A review on motion estimation in video compression

In modern world video compression technology is developed in to a bloomed field, with several techniques available for a wide range of applications like video transmission, HDTV, broadcast digitalvideo. Motion Estimation (ME) is a key component for high quality video compression, which is characterized by its high computation complexity and memory requirements. Motion Estimation has been conventionally used in the application of video encoding, but nowadays researchers from various fields other than video encoding are turning towards ME to solve various real time problems in their respective fields.

The main aim of the survey paper is to analyze ME in video compression techniques for video processing, especially to estimate how much amount of data to be compressed, which technique is faster and so on. We also compare video compression techniques with conventional methods like ES, ARP, Run length, and Huffman coding. The existing conventional techniques will be implemented on the MATLAB platform and the performance of video compression technique is evaluated with Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR) and search patterns.