Today several problems occur regarding video over internet. The solution of the problem is compression. The need for video compression is very important to minimize the storage space and transmission cost. There are several applications require video compression such as multimedia, internet, remote sensing etc. An Earlier method can be used for detection of visual and motion saliency in a compressed domain of video. However, nearest out of number of target is not considered .To deal with this depth saliency has been proposed for compressed video. Depth in an additional framework to help select the nearest out of a number of moving targets in a various multimedia application. A new fusion method of parameterized normalization, sum and product (PNSP) is designed to combine the results of saliency maps to get the final saliency map for each video frame. The proposed method provides the high compression ratio and high quality of video.The proposed model can predict the salient regions efficiently for video frames.
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video saliency detection, Regions of interest, video frames, video compression.