Video compression and decompression using adaptive rood pattern search

Abstract

Video compression is getting more and more important in the electronic world with increased amount of bandwidth and storage requirement due to increase in the video usage over the internet. Pioneering advances in the video compression algorithms is important. The project discusses various algorithms that are currently available in the commercial market for its advantages and disadvantages. One of them is H.264 standard. H.264 is a motion-block oriented codec standard developed by ITU-T. Aim of this algorithm is to provide better video quality with fewer amounts of information transfer. The final goal of the project was to implement a video encoder and decoder using Matlab. A video captured in RGB format was encoded using the encoder with each frame processed by dividing it into several motion-blocks. In the encoder part, several motion estimation algorithms were studied. The algorithms were compared with respect to number of calculations done by each algorithm and arithmetic complexity involved in them. Peak signal to noise ratio for multiple frames was also calculated for different algorithms to get information about quality of the algorithm. From the discussed algorithms, ARPS (Adaptive Rood Pattern Search) algorithm was used in the final encoder. Motion vectors generated by the ARPS were given to Motion Compensation to generate compensated image. The compensated image was transformed using DCT (Discrete Cosine Transform). Finally, the transformed vectors were Quantization and encoded using RLE (Run length encoding). The encoded video stream was successfully decoded by a decoder following reverse process to re-generate the video in its actual format.