Implementation of Adaptive Video Compression using Hybridized Wavelet Transform

Videos have been used for years but in current scenario video is one of the most use methods to represent information. In current time videos are not only used for communication and entertainment but also for education point of view, tutorials and lectures are also present in the form of video files. But difficulty with such a powerful media is its huge size, and it contains very large quantity of redundant data. Video holds memory in storage media and bandwidth over a communication medium (wireless or wired). The compression techniques are execute to shrink the size of the video but high compression ratio compromises the quality of the video (low PSNR value) when decompressed and it-s also a very lengthy procedure. The challenge is to propose an approach which gives a satisfactory high value of compression ratio and Peak Signal to Noise Ratio (PSNR). The wavelet transform is broadly applied compression technique but it gives a low PSNR value if we use an adaptive hybrid wavelet transformation system. The system uses the 3D-SPIHT (3D Set Partitioning in Hierarchical Trees) which uses the properties of wavelet transformed frames of the video to increase the efficiency, performance. And after that, the proposed system uses the RLE (Run Length Encoding) to add more compression ratio without and gives a better PSNR value which makes it more capable than DCT technique. To examine the values of compression ratio and PSNR can be calculated by simulating the system using MATLAB.