{"content":[{"text":"Chapter 9","bbox":{"left":0.148788,"top":0.138872,"width":0.12254000000000001,"height":0.025923}},{"text":"Image Prediction and Motion Compensation","bbox":{"left":0.299793,"top":0.138872,"width":0.540317,"height":0.025923}},{"text":"9.1 Introduction","bbox":{"left":0.142857,"top":0.181822,"width":0.197175,"height":0.025923}},{"text":"In previous chapters, we combined various well-developed techniques which are shown \n in Figure 7-1 to compress image data. You may be amazed to see that the techniques \n can achieve high compression ratios with high-quality reproduced decompressed images. \n Actually, the best is yet to come. So far, we have only considered static images and have \n used .ppm ﬁles in our examples; the techniques employed in Figure 7-1 have only exploited \n the correlations between pixels ( or spatial redundancy ). These techniques are very similar \n to those used by the JPEG standard to compress static images. Actually, they can be applied \n to encode a sequence of images, compressing each image individually. This method of \n compressing each frame independently is known as motion JPEG or M-JPEG. Obviously, \n M-JPEG has not made use of the correlations between frames ( temporal redundancy ) to \n achieve higher compression. M-JPEG is usually used in very high quality video captures \n and the scenes are normally captured in the raw data format which are then edited and \n compressed into another format. Encoding each frame individually is also referred to as \n intra-frame coding, where at a certain instance, data processing is applied only to the data \n of the current frame but not to any other frame in the video sequence. This contrasts with \n inter-frame coding, where processing is applied simultaneously to the data of the current \n frame and the adjacent frames. If you watch a movie played by a DVD player and at some \n point change it to play at a slow-motion mode, you would notice that most consecutive \n frames within a sequence are very similar to the frames both before and after the frame of \n interest. By exploiting the inherent temporal, or time-based redundancies between frames, \n considerably more compression efﬁciency can be obtained. \n Intra-frames are often referred to as I-frames and inter-frames are called P-frames. P \n here refers to ‘prediction’. This is because people use motion estimation and a technique \n known as block-based motion compensated prediction to exploit the temporal correlations \n between frames in order to reduce the redundancies. Indeed, in Chapter 2 we have dis- \n cussed that the information conveyed by a set of data closely relates to its predictability. A \n perfectly predictable message conveys no information. Actually, besides temporal predic- \n tion, we can also use spatial prediction to reduce data redundancies.","bbox":{"left":0.142857,"top":0.222813,"width":0.7142949999999999,"height":0.46499199999999996}},{"text":"9.2 Temporal Model","bbox":{"left":0.142857,"top":0.707738,"width":0.244853,"height":0.02592300000000003}},{"text":"A temporal model exploits inter-frame correlations to reduce redundancies. Very often, a \n predicted frame is calculated or formed by certain procedures and is subtracted from the \n current frame, producing a residual or difference frame. The more accurate the prediction, \n the less information the residual data contain and the higher compression we can achieve. \n The residual data are encoded in the usual way as presented in Figure 7-1. Besides decoding \n the encoded residual data, the decoder has to recreate the predicted frame and adds it to \n the decoded residual to reconstruct the current frame ( usually this is a lossy process; the \n reconstructed frame is not identical to the original one ). The predicted frame is often \n created from one or more past or future frames which are referred to as ‘reference frames’. \n Predictions in general can be improved by compensating for motion between the current \n frame and reference frames. We will discuss motion compensation in detail in the next \n section.","bbox":{"left":0.142857,"top":0.74873,"width":0.714283,"height":0.199322}},{"text":"1","bbox":{"left":0.495058,"top":0.966378,"width":0.009884000000000004,"height":0.016673999999999967}}],"images_bbox":[],"images_bbox_not_text_overlap":[]}