Both information from the color components and frequency domain representation of the corresponding blocks are used while forming the feature vectors . The proposed method is robust to some post processing operations such as Gauss blurring , additive white noise and JPEG compression as shown in the experimental results . The watermark bits are encoded by BCH code , and then embedded into the host by modulating the relationships between the selected DCT coefficients . Since the modulation is Jpeg compression like method , this approach improves the robustness against JPEG compression . Experimental results show good robustness against several image manipulations including Jpeg compression , noisy , low-pass filtering , shearing and so on . Finally , the authentication results are improved by a cross window . Experimental results illustrate that the watermarked image has good imperceptibility and could tolerate multiple cycles of JPEG compression . It is also sensitive to malicious manipulations and could localize those tampered regions correctly . Currently , the compression standard developed by Joint Photographic Experts Group ( JPEG ) is the widely used product for the compression of satellite images . Moreover , one of the important elements which influence the performance of JPEG compression standard is the nature of quantization table . The compression ratio and the decompressed image quality are determined all-together by the quantization table , and hence , the table strongly influences the whole compression performance . The decryption process is lossless preserving the original JPEG data . The experiments indicate that each share image is approximately the same size as the original JPEG image retaining the storage advantage provided by JPEG compression standard . Three extensions , one to improve the random appearance of the generated shares , another to obtain shares with asymmetric file sizes , and the third to generalize the scheme for n>2 share cases , are described as well . JPEG Compression scheme is a widely used form of compression technique which provides good compressed result . However , the standard JPEG decompression result usually contains some artifacts , such as Blocking artifacts , Gibbs artifacts , Staircase artifacts , etc . At low bit rate , JPEG compression scheme is known for blocking artifacts due to the quantization of the high order discrete cosine transform ( DCT ) coefficients . This artifact can be minimized by the application of subband coding . In this paper , a novel image watermarking scheme is proposed . With the combination of JPEG compression scheme , the watermark is embedded in to the host image by consideration of the relationship between the quantized pixels and the original pixels . Since the proposed scheme has a nice combination of JPEG compression , the proposed scheme has good robustness against JPEG compressions . “ Steganography in 3D Geometries and Images by Adjacent Bin Mapping ” presented by Wu and Dugelay introduces a new countermeasure to steganography detection through histogram characteristic function . JPEG compression format for images became the one that attracts steganographers the most . Rossi , Garzia , and Cusani return to the topic with “ Peak-Shaped-Based Steganographic Technique for JPEG Images . In this paper , we proposed a simple method to automatically localize signboard texts within JPEG mobile phone camera images . Taking into account the information provided by the Discrete Cosine Transform ( DCT ) used by the JPEG compression format , we delimitate the borders of the most important text region . This system is simple , reliable , affordable , easily implementable , and quick even working under architectures with low computational resources . The JPEG compression format provides a rich source of forensic traces that include quantization artifacts , fingerprints of the container format , and numerical particularities of JPEG compressors . Such a diverse set of cues serves as the basis for a forensic examiner to determine origin and authenticity of an image . The av erageparent-child coding gain is plotted as a function of encoding rate for a set of 18 512 512 natural images in Figure 1 . Results for both SPIHT with arithmetic coding ( SPIHT-AC ) and SPIHT without arithmetic coding ( SPIHT-NC ) are included . Results indicate that , for natural images , the parent-child coding gain is typically around 0.40 dB for SPIHT-NC , and 0.25 dB for SPIHT-AC . In a bit stream syntax ( syntax ) of the slice structure , the image compression data in the slice image compressed data , each slice image compression data , a slice header of each slice image compression data , the arithmetic coding process in slice start code , and then transmitted in units of and the code word register reset flag indicating whether a register value that indicates the state of the reset , the register reset flag is arithmetic encoding of only , the following transmission unit indicate that " do not perform a reset " or the to use a register value used at the start of decoding , and multiplexing the initial register values ​​of the register values ​​at that point . A slice header , the arithmetic coding , the encoded data , a digital signal The fifth method describes the compression of data encrypted with block ciphers . Finally , in the sixth method an arithmetic coding-based approach is exploited to efficiently compress the encrypted images . The proposed image encryption scheme operated in the prediction error domain is shown to be able to provide a reasonably high level of security . We also demonstrate that an arithmetic coding-based approach can be exploited to efficiently compress the encrypted images . More notably , the proposed compression approach applied to encrypted images is only slightly worse , in terms of compression efficiency , than the state-of-the-art lossless/lossy image coders , which take original , unencrypted images as inputs . The earlier introduced arithmetic coding idea has been generalized to a very broad and flexible coding technique which includes virtually all known variable rate noiseless coding techniques as special cases . An outstanding feature of this technique is that alphabet extensions are not required . This paper describes the principles of Arithmetic coding along with its advantages compared to Huffman coding method . Problems of arithmetic coding implementation , due to the restriction of the floating point processing either on encoder nor decoder , are discussed as well with the suggested solution , i.e.modification of arithmetic coding using numerical integer . As the final conclusion , the algorithm is outstanding for the use of data compression matters . This data compression efficiency can be implicitly achieved by iteratively updating probability models stored in the embedded memory for hardware design . Therefore the design of the memory hierarchy and the suitable architecture is an important issue so that the power consumption can be kept low caused by memory accesses for iteratively executing arithmetic coding operations . To address the low power consideration for designing a CABAC encoder , we propose the architecture by using variable length tag cache memory scheme and pipeline structure . During the first half of this project , they designed a new compression algorithm called FPC for scientific double-precision data , made the source code available on the web , and published two papers describing its operation , the first in the proceedings of the Data Compression Conference and the second in the IEEE Transactions on Computers . At comparable average compression ratios , this algorithm compresses and decompresses 10 to 100 times faster than BZIP2 , DFCM , FSD , GZIP , and PLMI on the three architectures tested . With prediction tables that fit into the CPU 's L1 data acache , FPC delivers a guaranteed throughput of six gigabits per second on a 1.6 GHz Itanium 2 system . Additional features of the algorithm are efficient coding of the metadata ( such as probability distributions ) , as well as data relabeling in order to cope with large datasets and alphabets . We test the algorithm on several datasets , and demonstrate an improvement in the compression rates of between 2X and 5X compared to gzip . The larger improvements are observed for very large datasets , such as the Criteo click prediction dataset which was published as part of a recent Kaggle competition . We introduce a new lossless non-reference-based fastq compression algorithm named lossless FastQ compressor . We have compared our algorithm with other state of the art big data compression algorithms namely gzip , bzip2 , fastqz , fqzcomp , G-SQZ , SCALCE , Quip , DSRC , DSRC-LZ etc . This comparison reveals that our algorithm achieves better compression ratios . In HTTP , content codings allow for payload encodings such as for compression or integrity checks . In particular , the " gzip " content coding is widely used for payload data sent in response messages . Content codings can be used in request messages as well ; however , discoverability is not on par with response messages . Unlike previous attempts to design hardware-based encoders [ 5 , 6 ] , the design is compliant with GZIP specification and includes all three of the GZIP compression modes . Files compressed in hardware can be decompressed with the software version of GZIP . The flexibility of the design allows for hardware-based implementations using either FPGAs or ASICs . Next we show on the example of our gzip implementation how an engineer without previous MaxJ experience can quickly develop and optimize a real , complex application . The gzip design in MaxJ presented here took only one man-month to develop and achieved better performance than the related work created in Verilog and OpenCL . Since a MapReduce cloud is the key to the success of the large-scale computation , cloud computing can use the Smart MapReduce Cloud ( SMRC ) proposed in this paper to apply extra processing to intermediate data on demand while intermediate data is delivered among computers in the MapReduce cloud . In experiments , cloud computing is tested with several popular MapReduce applications to observe performances of data encryption and compression via XOR and GZIP functions in SMRC . With the view of coming out with the best technique and applying it to the GSMtext messages .But the text compression and decompression in mobile phones are different from text compression and decompression in desktops , laptops etc , therefore GZip(GNUzip ) which was designed based on the techniques above as an improved technique was used since compression To save energy while copying files , it is important to use APIs with tunable buffer sizes , rather than APIs using fixed size buffers . In addition , there is a trade off between compression ratio and energy cost : because of more compression ratio , xz compression API consumes more energy than zip and gzip compression APIs . Finally , we model the energy costs of APIs by polynomial regression to avoid repeated measurements . Our experiments show that we can be consistently smaller than the tree structure compression carried out by XMill , using the same backend compressors as XMill on our encodings . However , the most surprising result is that our own Huffman-like encoding of the grammars ( without any backend compressor whatsoever ) consistently outperforms XMill with gzip backend . This is of particular interest because our Huffman-like encoding can be queried without prior decompression . Consequently , we propose delta coding to compress the current virtual-machine memory dump by coding its differences with respect to a predicted memory image , with the latter formed by duplicating the loading of the executables and libraries into the baseline memory , resulting in a significant improvement in compression performance over straightforward delta coding alone . In experimental results for a body of malware samples , the proposed approach outperformed the widely used xdelta3 delta coder by approximately 20 % and the popular generic gzip coder by 79 % . Dengan mengeluarkan biaya , yang tentunya tidak sedikit , atau dengan cuma-cuma ? Penulis ingin menggunakan cara yang efektif , gratis , dan bisa diterapkan untuk menyembunyikan kode PHP ini , yaitu dengan fasilitas yang sudah ada pada PHP , yaitu 3DES sebagai metode enkripsi , gzip sebagai metode kompresi , dan base64 sebagai penyusunan ulang kode . Dan setelah kode PHP ini disembunyikan , tentunya script PHP harus masih bisa memenuhi tugasnya , yaitu berjalan sesuai dengan fungsinya . At the receiving end different opposite processes should run to get the back the original secret message . This paper mainly discuss about Image compression and decompression technique based on Block Truncation Coding ( BTC ) and perform data hiding mechanism in decompressed image and also discuss to retrieve the minimum pixels image such as 8 × 8 pixels , 16 × 16 pixels and so on , up to original cover image size through the divided by 2 × 2 pixels and perform data hiding in retrieve image . The discrete-cosine-transform coding ( DCT ) , which is efficient for a part having small gray-level variation , is applied to a block having no sharp edge . The block-truncation coding ( BTC ) which preserves sharp edges is applied to a block having edges , and then the DCT is applied to their error images . This combined procedure makes a reconstruction of the whole image in a high quality . Techniques for achieving data compression can be divided into two basic approaches : spatial coding and Transform coding . This report presents a method for the compression of digital images using hybrid compression method based on Block Truncation Coding ( BTC ) and Walsh Hadamard Transform (WHT).The objective of this hybrid approach is to achieve higher compression ratio by applying BTC and WHT . Several gray-scale test images are used to evaluate the coding efficiency and performance of the hybrid method and compared with the BTC and WHT respectively . In the new approach , an image is segmented into blocks of various sizes . The block truncation code ( BTC ) of an image block consists of two gray levels and a binary mask . A vector quantization scheme is used to generate a codebook of fixed size vectors which serves as the set of representative masks of all blocks of different sizes . One way to reduce waste of memory is to perform image compression . One of the compression algorithm can be used is a Block Truncation Code ( BTC ) . BTC algorithm has good ability to compress an image with the complexity of the algorithm is not so difficult . One how to less waste of memory is to perform compres- sion image . One of the compression algorithms that can be used is Block Truncation Code ( BTC ) . BTC algorithm has good ability to compress a image with the complexity of the algorithm that is not so dicult . In this paper , we have presented a method named Improved Adaptive Block Truncation Coding ( IABTC ) based on the Adaptive Block Truncation Coding ( ABTC ) method . Few other existing Block Truncation Coding ( BTC ) based methods are discussed in Section 2 . The proposed method is explained in Section 3 . This paper presents a block truncation coding ( BTC ) scheme for image compression that employs visual patterns designed independently of the image to be coded . In this method , image blocks are first classified into three classes : uniform , gentle edge , and sharp edge , according to their variations . In this paper , a discussion of compression and encoding approaches is done . The paper also discussed some of the effective compression based techniques so that the effective and reliable communication will be drawn . In the second step , we have implemented a k-nearest neighbours algorithm providing 85 % as accuracy rate . Coupled with other anti-spam techniques , compression-based methods could bring a great help in the spam filtering challenge . Comparing these compression distances with listeners ’ similarity ratings between pairs of melodies collected in three experiments demonstrates that the compression-based model provides a good fit to the data and allows the identification of representations , model parameters and compression-based metrics that best account for musical similarity perception . The compression-based model also shows comparable performance to the best-performing algorithms on the MIREX 2005 melodic similarity task . MPEG-4 includes several extensions compared to MPEG-1 and -2 especially in terms of object-based interactivity . In addition to advanced A/V compression methods ( MPEG-4 Part2 , Part3 and Part 10 ) , MPEG-4 Part1 , which is named " Systems " , contains additional tools such as binary/textual file format , multiplexing , synchronization scheme , scene description , etc . The use of MPEG-4 can resolve the problem of format diversity while providing high interactivity to users . The thesis contemplates two directions for power savings in the interconnection network ; one is the possibility to use lower bandwidth links during the communication phases and thus save energy , while the second one addresses shifting links to low-power mode during computation phases when they are unused . To address the first one we investigate the potential benefits from MPI data compression . When compression of MPI data is possible , the reduction in link bandwidth is enabled without incurring any performance penalty . Whereas HPC interconnects have traditionally been designed with a focus on bandwidth and latency , there is an increasing interest in minimising the interconnect 's energy consumption . This paper complements ongoing efforts related to power reduction and energy proportionality , by investigating the potential benefits from MPI data compression . We apply lossy compression to two common communication patterns in HPC kernels , in conjunction with recently introduced InfiniBand ( IB ) power saving modes . Moreover , the three parameters which affect the quality of image compression are analyzed . The verification experiments to ADV212 compression system show that compression system works fast and stably . The time needed in compressing a frame image is only 7.68 ms , all PSNRs are more than 30 dB in the compression ratio of 2:1 to 32:1,and the average PSNR is increased by 2.49 dB in the lossy compression mode when the compression ratio is 1 bpp . A ( 10 , 5 ) setting the quantization step method was proposed , This method makes the rate control error reduces 16.385 % . Finally , the verification experiments to ADV212 compression system using ground test equipment were carried out . The experiments results showed that compression system can be fast and stable work . However , there are gaps inevitably between telescopes , which degrade the results of aperture synthesis . In this work , the effect of gaps on the instantaneous Doppler spectrum of each channel and the influence on the result of the azimuth impulse compression after aperture synthesis are analyzed . In addition , an estimation method of gaps based on the phase errors between channels is proposed to reduce the influence . At the decoder , an inverse WDCT is performed to reconstruct the image . The WDCT based compression outperforms the DCT based compression , for high bit rate applications and for images with high-frequency components . It results in 1.1 - 3.1-dB PSNR gain over conventional DCT at 1.5 bpp for natural images , and provides more gain for compound images with texts . This feature allowed oursimulation methodology compression methodology that allows forrandom accessdecomprestohaveanaverage speedupof9.67times compared totheexist-sion[3 ] . Randomaccess decompression isatermusedtodescribe a ingstate ofthearttool ( Dinero IVcache simulator ) , forarangeof compression methodology that allows thedecompression tostart at applications from theMediabench suite . anypoint inthecompressed file . This correspondence presents an image compression ap- proach that integrates our proposed parameter-assistant inpainting ( PAI ) to exploit visual redundancy in color images . In this scheme , we study different distributions of image regions and represent them with a model class . This paper describes an approach intermediate between those two : it is based on token clustering , but additionally groups tokens into candidate fonts . Our approach has the potential of yielding OCR-like PDFs when the inputs are high quality and degrading to token based compression when the font analysis fails , while preserving full visual fidelity . Our approach is based on an unsupervised algorithm for grouping tokens into candidate fonts . This paper considers lossless compression of black and white images using recently developed distributed turbo compression techniques . An empirical study of image pixel statistics is initially conducted in order to apply turbo compression algorithms to distributed compression of image rows . From the discovered textual pattern , we derived some heuristic Sentence Compression Rules in generating compressed sentences to construct a single extract Malay summary . We conducted experiments on Malay news dataset and the result demonstrates that moderate compressed summary using Sentence Compression Rules has better agreement with human composed summary . Since there is growth in the traffic of communications systems , development of spectrally efficient transmission systems are necessary . To design a spectrally efficient communication system requires minimising the speech transmission bit rate using speech compression ( or coding ) techniques . There has been considerable interest in the development of low bit rate , high quality speech coding systems . Thus , after the scale is set , we adjust the value of cardinality and width to maintain the overall model complexity similar to its counterparts . We do not focus on reducing the model size in this work since it requires more meticulous designs such as depth - wise separable convolution , model pruning , and model compression . For experiments on the ImageNet dataset , due to our limited computational resources , we mainly use the ResNet - 50 , ResNeXt - 50 and DLA - 60 In practice , we increase efficiency by indexing all pairs , and updating data structures incrementally . The main difference to other compression algorithms , such as Huffman encoding , which have been proposed to produce a variable - length encoding of words for NMT [ reference ] , is that our symbol sequences are still interpretable as subword units , and that the network can generalize to translate and produce new words ( unseen at training time ) on the basis of these subword units . Figure 1 shows a toy example of learned BPE operations . This property allows us great freedom in the choice of tokens ’ unit . Neural networks have been shown to work well with word tokens but also with finer units , such as subwords as well as symbols resulting from compression / encoding . Although there have been a number of previous research reporting the use of neural networks with characters ( see , e.g. , mikolov2012subword and santos2014learning ) , the dominant approach has been to preprocess the text into a sequence of symbols , each associated with a sequence of characters , after which the neural network is presented with those symbols rather than with characters . In this section , we carry out deblocking experiments to recover high quality images from their JPEG compression . As in other compression artifacts reduction methods , standard JPEG compression schemes of JPEG quality settings and in MATLAB JPEG encoder are used . The LIVE1 dataset is used for evaluation , and we have compared our method with AR - CNN , SA - DCT and deeper SRCNN .
Both information from the color components and frequency domain representation of the corresponding blocks are used while forming the feature vectors . The proposed method is robust to some post processing operations such as Gauss blurring , additive white noise and JPEG compression as shown in the experimental results .
The watermark bits are encoded by BCH code , and then embedded into the host by modulating the relationships between the selected DCT coefficients . Since the modulation is Jpeg compression like method , this approach improves the robustness against JPEG compression . Experimental results show good robustness against several image manipulations including Jpeg compression , noisy , low-pass filtering , shearing and so on .
Finally , the authentication results are improved by a cross window . Experimental results illustrate that the watermarked image has good imperceptibility and could tolerate multiple cycles of JPEG compression . It is also sensitive to malicious manipulations and could localize those tampered regions correctly .
Currently , the compression standard developed by Joint Photographic Experts Group ( JPEG ) is the widely used product for the compression of satellite images . Moreover , one of the important elements which influence the performance of JPEG compression standard is the nature of quantization table . The compression ratio and the decompressed image quality are determined all-together by the quantization table , and hence , the table strongly influences the whole compression performance .
The decryption process is lossless preserving the original JPEG data . The experiments indicate that each share image is approximately the same size as the original JPEG image retaining the storage advantage provided by JPEG compression standard . Three extensions , one to improve the random appearance of the generated shares , another to obtain shares with asymmetric file sizes , and the third to generalize the scheme for n>2 share cases , are described as well .
JPEG Compression scheme is a widely used form of compression technique which provides good compressed result . However , the standard JPEG decompression result usually contains some artifacts , such as Blocking artifacts , Gibbs artifacts , Staircase artifacts , etc .
At low bit rate , JPEG compression scheme is known for blocking artifacts due to the quantization of the high order discrete cosine transform ( DCT ) coefficients . This artifact can be minimized by the application of subband coding .
In this paper , a novel image watermarking scheme is proposed . With the combination of JPEG compression scheme , the watermark is embedded in to the host image by consideration of the relationship between the quantized pixels and the original pixels . Since the proposed scheme has a nice combination of JPEG compression , the proposed scheme has good robustness against JPEG compressions .
“ Steganography in 3D Geometries and Images by Adjacent Bin Mapping ” presented by Wu and Dugelay introduces a new countermeasure to steganography detection through histogram characteristic function . JPEG compression format for images became the one that attracts steganographers the most . Rossi , Garzia , and Cusani return to the topic with “ Peak-Shaped-Based Steganographic Technique for JPEG Images .
In this paper , we proposed a simple method to automatically localize signboard texts within JPEG mobile phone camera images . Taking into account the information provided by the Discrete Cosine Transform ( DCT ) used by the JPEG compression format , we delimitate the borders of the most important text region . This system is simple , reliable , affordable , easily implementable , and quick even working under architectures with low computational resources .
The JPEG compression format provides a rich source of forensic traces that include quantization artifacts , fingerprints of the container format , and numerical particularities of JPEG compressors . Such a diverse set of cues serves as the basis for a forensic examiner to determine origin and authenticity of an image .
The av erageparent-child coding gain is plotted as a function of encoding rate for a set of 18 512 512 natural images in Figure 1 . Results for both SPIHT with arithmetic coding ( SPIHT-AC ) and SPIHT without arithmetic coding ( SPIHT-NC ) are included . Results indicate that , for natural images , the parent-child coding gain is typically around 0.40 dB for SPIHT-NC , and 0.25 dB for SPIHT-AC .
In a bit stream syntax ( syntax ) of the slice structure , the image compression data in the slice image compressed data , each slice image compression data , a slice header of each slice image compression data , the arithmetic coding process in slice start code , and then transmitted in units of and the code word register reset flag indicating whether a register value that indicates the state of the reset , the register reset flag is arithmetic encoding of only , the following transmission unit indicate that " do not perform a reset " or the to use a register value used at the start of decoding , and multiplexing the initial register values ​​of the register values ​​at that point . A slice header , the arithmetic coding , the encoded data , a digital signal
The fifth method describes the compression of data encrypted with block ciphers . Finally , in the sixth method an arithmetic coding-based approach is exploited to efficiently compress the encrypted images .
The proposed image encryption scheme operated in the prediction error domain is shown to be able to provide a reasonably high level of security . We also demonstrate that an arithmetic coding-based approach can be exploited to efficiently compress the encrypted images . More notably , the proposed compression approach applied to encrypted images is only slightly worse , in terms of compression efficiency , than the state-of-the-art lossless/lossy image coders , which take original , unencrypted images as inputs .
The earlier introduced arithmetic coding idea has been generalized to a very broad and flexible coding technique which includes virtually all known variable rate noiseless coding techniques as special cases . An outstanding feature of this technique is that alphabet extensions are not required .
This paper describes the principles of Arithmetic coding along with its advantages compared to Huffman coding method . Problems of arithmetic coding implementation , due to the restriction of the floating point processing either on encoder nor decoder , are discussed as well with the suggested solution , i.e.modification of arithmetic coding using numerical integer . As the final conclusion , the algorithm is outstanding for the use of data compression matters .
This data compression efficiency can be implicitly achieved by iteratively updating probability models stored in the embedded memory for hardware design . Therefore the design of the memory hierarchy and the suitable architecture is an important issue so that the power consumption can be kept low caused by memory accesses for iteratively executing arithmetic coding operations . To address the low power consideration for designing a CABAC encoder , we propose the architecture by using variable length tag cache memory scheme and pipeline structure .
During the first half of this project , they designed a new compression algorithm called FPC for scientific double-precision data , made the source code available on the web , and published two papers describing its operation , the first in the proceedings of the Data Compression Conference and the second in the IEEE Transactions on Computers . At comparable average compression ratios , this algorithm compresses and decompresses 10 to 100 times faster than BZIP2 , DFCM , FSD , GZIP , and PLMI on the three architectures tested . With prediction tables that fit into the CPU 's L1 data acache , FPC delivers a guaranteed throughput of six gigabits per second on a 1.6 GHz Itanium 2 system .
Additional features of the algorithm are efficient coding of the metadata ( such as probability distributions ) , as well as data relabeling in order to cope with large datasets and alphabets . We test the algorithm on several datasets , and demonstrate an improvement in the compression rates of between 2X and 5X compared to gzip . The larger improvements are observed for very large datasets , such as the Criteo click prediction dataset which was published as part of a recent Kaggle competition .
We introduce a new lossless non-reference-based fastq compression algorithm named lossless FastQ compressor . We have compared our algorithm with other state of the art big data compression algorithms namely gzip , bzip2 , fastqz , fqzcomp , G-SQZ , SCALCE , Quip , DSRC , DSRC-LZ etc . This comparison reveals that our algorithm achieves better compression ratios .
In HTTP , content codings allow for payload encodings such as for compression or integrity checks . In particular , the " gzip " content coding is widely used for payload data sent in response messages . Content codings can be used in request messages as well ; however , discoverability is not on par with response messages .
Unlike previous attempts to design hardware-based encoders [ 5 , 6 ] , the design is compliant with GZIP specification and includes all three of the GZIP compression modes . Files compressed in hardware can be decompressed with the software version of GZIP . The flexibility of the design allows for hardware-based implementations using either FPGAs or ASICs .
Next we show on the example of our gzip implementation how an engineer without previous MaxJ experience can quickly develop and optimize a real , complex application . The gzip design in MaxJ presented here took only one man-month to develop and achieved better performance than the related work created in Verilog and OpenCL .
Since a MapReduce cloud is the key to the success of the large-scale computation , cloud computing can use the Smart MapReduce Cloud ( SMRC ) proposed in this paper to apply extra processing to intermediate data on demand while intermediate data is delivered among computers in the MapReduce cloud . In experiments , cloud computing is tested with several popular MapReduce applications to observe performances of data encryption and compression via XOR and GZIP functions in SMRC .
With the view of coming out with the best technique and applying it to the GSMtext messages .But the text compression and decompression in mobile phones are different from text compression and decompression in desktops , laptops etc , therefore GZip(GNUzip ) which was designed based on the techniques above as an improved technique was used since compression
To save energy while copying files , it is important to use APIs with tunable buffer sizes , rather than APIs using fixed size buffers . In addition , there is a trade off between compression ratio and energy cost : because of more compression ratio , xz compression API consumes more energy than zip and gzip compression APIs . Finally , we model the energy costs of APIs by polynomial regression to avoid repeated measurements .
Our experiments show that we can be consistently smaller than the tree structure compression carried out by XMill , using the same backend compressors as XMill on our encodings . However , the most surprising result is that our own Huffman-like encoding of the grammars ( without any backend compressor whatsoever ) consistently outperforms XMill with gzip backend . This is of particular interest because our Huffman-like encoding can be queried without prior decompression .
Consequently , we propose delta coding to compress the current virtual-machine memory dump by coding its differences with respect to a predicted memory image , with the latter formed by duplicating the loading of the executables and libraries into the baseline memory , resulting in a significant improvement in compression performance over straightforward delta coding alone . In experimental results for a body of malware samples , the proposed approach outperformed the widely used xdelta3 delta coder by approximately 20 % and the popular generic gzip coder by 79 % .
Dengan mengeluarkan biaya , yang tentunya tidak sedikit , atau dengan cuma-cuma ? Penulis ingin menggunakan cara yang efektif , gratis , dan bisa diterapkan untuk menyembunyikan kode PHP ini , yaitu dengan fasilitas yang sudah ada pada PHP , yaitu 3DES sebagai metode enkripsi , gzip sebagai metode kompresi , dan base64 sebagai penyusunan ulang kode . Dan setelah kode PHP ini disembunyikan , tentunya script PHP harus masih bisa memenuhi tugasnya , yaitu berjalan sesuai dengan fungsinya .
At the receiving end different opposite processes should run to get the back the original secret message . This paper mainly discuss about Image compression and decompression technique based on Block Truncation Coding ( BTC ) and perform data hiding mechanism in decompressed image and also discuss to retrieve the minimum pixels image such as 8 × 8 pixels , 16 × 16 pixels and so on , up to original cover image size through the divided by 2 × 2 pixels and perform data hiding in retrieve image .
The discrete-cosine-transform coding ( DCT ) , which is efficient for a part having small gray-level variation , is applied to a block having no sharp edge . The block-truncation coding ( BTC ) which preserves sharp edges is applied to a block having edges , and then the DCT is applied to their error images . This combined procedure makes a reconstruction of the whole image in a high quality .
Techniques for achieving data compression can be divided into two basic approaches : spatial coding and Transform coding . This report presents a method for the compression of digital images using hybrid compression method based on Block Truncation Coding ( BTC ) and Walsh Hadamard Transform (WHT).The objective of this hybrid approach is to achieve higher compression ratio by applying BTC and WHT . Several gray-scale test images are used to evaluate the coding efficiency and performance of the hybrid method and compared with the BTC and WHT respectively .
In the new approach , an image is segmented into blocks of various sizes . The block truncation code ( BTC ) of an image block consists of two gray levels and a binary mask . A vector quantization scheme is used to generate a codebook of fixed size vectors which serves as the set of representative masks of all blocks of different sizes .
One way to reduce waste of memory is to perform image compression . One of the compression algorithm can be used is a Block Truncation Code ( BTC ) . BTC algorithm has good ability to compress an image with the complexity of the algorithm is not so difficult .
One how to less waste of memory is to perform compres- sion image . One of the compression algorithms that can be used is Block Truncation Code ( BTC ) . BTC algorithm has good ability to compress a image with the complexity of the algorithm that is not so dicult .
In this paper , we have presented a method named Improved Adaptive Block Truncation Coding ( IABTC ) based on the Adaptive Block Truncation Coding ( ABTC ) method . Few other existing Block Truncation Coding ( BTC ) based methods are discussed in Section 2 . The proposed method is explained in Section 3 .
This paper presents a block truncation coding ( BTC ) scheme for image compression that employs visual patterns designed independently of the image to be coded . In this method , image blocks are first classified into three classes : uniform , gentle edge , and sharp edge , according to their variations .
In this paper , a discussion of compression and encoding approaches is done . The paper also discussed some of the effective compression based techniques so that the effective and reliable communication will be drawn .
In the second step , we have implemented a k-nearest neighbours algorithm providing 85 % as accuracy rate . Coupled with other anti-spam techniques , compression-based methods could bring a great help in the spam filtering challenge .
Comparing these compression distances with listeners ’ similarity ratings between pairs of melodies collected in three experiments demonstrates that the compression-based model provides a good fit to the data and allows the identification of representations , model parameters and compression-based metrics that best account for musical similarity perception . The compression-based model also shows comparable performance to the best-performing algorithms on the MIREX 2005 melodic similarity task .
MPEG-4 includes several extensions compared to MPEG-1 and -2 especially in terms of object-based interactivity . In addition to advanced A/V compression methods ( MPEG-4 Part2 , Part3 and Part 10 ) , MPEG-4 Part1 , which is named " Systems " , contains additional tools such as binary/textual file format , multiplexing , synchronization scheme , scene description , etc . The use of MPEG-4 can resolve the problem of format diversity while providing high interactivity to users .
The thesis contemplates two directions for power savings in the interconnection network ; one is the possibility to use lower bandwidth links during the communication phases and thus save energy , while the second one addresses shifting links to low-power mode during computation phases when they are unused . To address the first one we investigate the potential benefits from MPI data compression . When compression of MPI data is possible , the reduction in link bandwidth is enabled without incurring any performance penalty .
Whereas HPC interconnects have traditionally been designed with a focus on bandwidth and latency , there is an increasing interest in minimising the interconnect 's energy consumption . This paper complements ongoing efforts related to power reduction and energy proportionality , by investigating the potential benefits from MPI data compression . We apply lossy compression to two common communication patterns in HPC kernels , in conjunction with recently introduced InfiniBand ( IB ) power saving modes .
Moreover , the three parameters which affect the quality of image compression are analyzed . The verification experiments to ADV212 compression system show that compression system works fast and stably . The time needed in compressing a frame image is only 7.68 ms , all PSNRs are more than 30 dB in the compression ratio of 2:1 to 32:1,and the average PSNR is increased by 2.49 dB in the lossy compression mode when the compression ratio is 1 bpp .
A ( 10 , 5 ) setting the quantization step method was proposed , This method makes the rate control error reduces 16.385 % . Finally , the verification experiments to ADV212 compression system using ground test equipment were carried out . The experiments results showed that compression system can be fast and stable work .
However , there are gaps inevitably between telescopes , which degrade the results of aperture synthesis . In this work , the effect of gaps on the instantaneous Doppler spectrum of each channel and the influence on the result of the azimuth impulse compression after aperture synthesis are analyzed . In addition , an estimation method of gaps based on the phase errors between channels is proposed to reduce the influence .
At the decoder , an inverse WDCT is performed to reconstruct the image . The WDCT based compression outperforms the DCT based compression , for high bit rate applications and for images with high-frequency components . It results in 1.1 - 3.1-dB PSNR gain over conventional DCT at 1.5 bpp for natural images , and provides more gain for compound images with texts .
This feature allowed oursimulation methodology compression methodology that allows forrandom accessdecomprestohaveanaverage speedupof9.67times compared totheexist-sion[3 ] . Randomaccess decompression isatermusedtodescribe a ingstate ofthearttool ( Dinero IVcache simulator ) , forarangeof compression methodology that allows thedecompression tostart at applications from theMediabench suite . anypoint inthecompressed file .
This correspondence presents an image compression ap- proach that integrates our proposed parameter-assistant inpainting ( PAI ) to exploit visual redundancy in color images . In this scheme , we study different distributions of image regions and represent them with a model class .
This paper describes an approach intermediate between those two : it is based on token clustering , but additionally groups tokens into candidate fonts . Our approach has the potential of yielding OCR-like PDFs when the inputs are high quality and degrading to token based compression when the font analysis fails , while preserving full visual fidelity . Our approach is based on an unsupervised algorithm for grouping tokens into candidate fonts .
This paper considers lossless compression of black and white images using recently developed distributed turbo compression techniques . An empirical study of image pixel statistics is initially conducted in order to apply turbo compression algorithms to distributed compression of image rows .
From the discovered textual pattern , we derived some heuristic Sentence Compression Rules in generating compressed sentences to construct a single extract Malay summary . We conducted experiments on Malay news dataset and the result demonstrates that moderate compressed summary using Sentence Compression Rules has better agreement with human composed summary .
Since there is growth in the traffic of communications systems , development of spectrally efficient transmission systems are necessary . To design a spectrally efficient communication system requires minimising the speech transmission bit rate using speech compression ( or coding ) techniques . There has been considerable interest in the development of low bit rate , high quality speech coding systems .
Thus , after the scale is set , we adjust the value of cardinality and width to maintain the overall model complexity similar to its counterparts . We do not focus on reducing the model size in this work since it requires more meticulous designs such as depth - wise separable convolution , model pruning , and model compression . For experiments on the ImageNet dataset , due to our limited computational resources , we mainly use the ResNet - 50 , ResNeXt - 50 and DLA - 60
In practice , we increase efficiency by indexing all pairs , and updating data structures incrementally . The main difference to other compression algorithms , such as Huffman encoding , which have been proposed to produce a variable - length encoding of words for NMT [ reference ] , is that our symbol sequences are still interpretable as subword units , and that the network can generalize to translate and produce new words ( unseen at training time ) on the basis of these subword units . Figure 1 shows a toy example of learned BPE operations .
This property allows us great freedom in the choice of tokens ’ unit . Neural networks have been shown to work well with word tokens but also with finer units , such as subwords as well as symbols resulting from compression / encoding . Although there have been a number of previous research reporting the use of neural networks with characters ( see , e.g. , mikolov2012subword and santos2014learning ) , the dominant approach has been to preprocess the text into a sequence of symbols , each associated with a sequence of characters , after which the neural network is presented with those symbols rather than with characters .
In this section , we carry out deblocking experiments to recover high quality images from their JPEG compression . As in other compression artifacts reduction methods , standard JPEG compression schemes of JPEG quality settings and in MATLAB JPEG encoder are used . The LIVE1 dataset is used for evaluation , and we have compared our method with AR - CNN , SA - DCT and deeper SRCNN .
A hybrid image authentication method robust to JPEG attacks Robust oblivious image watermarking scheme based on coefficient relation A Novel Semi-fragile Authentication Watermarking Scheme of Color JPEG Image in Compressed Domain Optimal quantization table generation for efficient satellite image compression using teaching learning based optimization technique Shared key encryption of JPEG color images Artifacts Removal in JPEG Decompression via learned dictionary and Total variation regularization Practical implementation of subband DCT based coder Self-reference based semi-fragile image watermarking scheme for authentication Secure Steganography in Multimedia Content Simple and Efficient Text Localization for Compressed Image in Mobile Phone Image Forensics from Chroma Subsampling of High-Quality JPEG Images On Parent-Child Coding Gain in Zero-Tree Based Coders Digital signal encoding device, digital signal decoding device, digital signal arithmetic encoding method, and digital signal arithmetic decoding method A SURVEY ON DIFFERENT COMPRESSION TECHNIQUES FOR EFFICIENT IMAGE TRANSFER Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation Arithmetic Coding Studi Kompresi Data Dengan Metode Arithmetic Coding Design of a Low Power Architecture for CABAC Encoder in H.264 Portable and Transparent Message Compression in MPI Libraries to Improve the Performance and Scalability of Parallel Applications Compressing Tabular Data via Pairwise Dependencies RETRACTED: LFQC: a lossless compression algorithm for FASTQ files Hypertext Transfer Protocol (HTTP) Client-Initiated Content-Encoding FPGA-Based Lossless Data Compression Using GNU Zip Rapid Development of Gzip with MaxJ Smart MapReduce cloud: Applying extra processing to intermediate data on demand Application of data compression technique to gsm text messages Impact of Developer Choices on Energy Consumption of Software on Servers XML Tree Structure Compression Delta Encoding of Virtual-Machine Memory in the Dynamic Analysis of Malware Aplikasi Pengamanan Kode Sumber (Source Code) PHP Yang Disimpan Pada Public Hosting Service Menggunakan Algoritma Kompresi LZW Dan Enkripsi 3DES Image Compression and Decompression Technique Based on Block Truncation Coding (BTC) And Perform Data Hiding Mechanism in Decompressed Image A compression algorithm for medical images and a display with the decoding function hybrid image compression technique Image compression by vector quantized hierarchical block truncation codes BLOCK TRUNCATION ALGORITHM CODING (BTC) IN DIGITAL IMAGE COMPRESSION USED MATLAB 7.0 ALGORITHM BLOCK TRUNCTION CODING (BTC) IN DIGITAL IMAGE COMPRESSION BY USING MATLAB 7.0 Improved Adaptive Block Truncation Coding for Image Compression BTC image coding with visual patterns Discussion of Effective Speech Communication under Different Compression Approaches Spam filtering using Kolmogorov complexity analysis Compression-based Modelling of Musical Similarity Perception MPEG-4 systems based authoring for 3D visual content MPI layer techniques to improve network energy efficiency Analyzing Performance Improvements and Energy Savings in Infiniband Architecture using Network Compression High Performance ADV212 Controller for Applications of the Large Field of View TDICCD Space Camera [Application of ADV212 to the large field of view multi-spectral TDICCD space camera]. Analysis and compensation of telescopes' gaps effect on aperture synthesis in a multi-channel synthetic aperture ladar system. Warped discrete cosine transform and its application in image compression Instruction TraceCompression forRapidInstruction CacheSimulation Block-Based Image Compression With Unsupervised font reconstruction based on token co-occurrence On turbo-compression and modeling of black and white images A Malay text summarizer using pattern-growth method with sentence compression rules Sinusoidal Model Based Low Bit Rate Speech Coding for Communication Systems. Res2Net: A New Multi-scale Backbone Architecture Neural Machine Translation of Rare Words with Subword Units A Character-level Decoder without Explicit Segmentation for Neural Machine Translation Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
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