A Remote Educational Video Dynamic Image Sharp Processing Algorithm
In distance education network transmission process, because transmission distance is too long, transmission network will be affected by complicated external environment factors, which leads to network failure and failure in remote education video image formation, and finally causes unsmooth transmission. This paper puts forward a distributed network fault detection technology to perform fault detection for remote education transmission network nodes and characteristic analysis of the use of network fault by using genetic neural network, accurately locate fault node area so as to realize the remote education networks fault detection. Experiments show that this method can avoid distance education network fault resulted from long transmission distance and improve the transmission efficiency of remote education video image.