Studies on edge detection based video compression techniques using hog descriptors

Abstract

Recently, the escalating requirement to transform video information into mobile communication services, surveillance services, and the multimedia industry has made a needy high efficient video processing technology. Conversely, the data rates of digital image/video are large volume, which occupies wider bandwidth, increased storage capacity and computational complexity in the distinctive computing devices. In order to bridge the demanding services, advanced video coding schemes have been enhanced to avoid spatial, spectral and temporal redundancies, enabling efficient and higher rate of transmission of digital video sequences and also to carry volume of information in a compressed manner. There are three distinct domain have experienced enormous development and huge marketable growth such as video surveillance, multimedia technology and wireless mobile networks. This type of enhancements basically requires a less complex, good energy consumption and higher rate of information access freedom with highly acceptable quality of service. Consequently, the latest research findings have been targeted to achieve sensible gains by strengthening image and video coding efficiency and also keeping complexity reduction. Many of the service providers and every end user are finding for better standards and plug-ins with high efficiency for high definition visual effect even after reception while transmitting with limited channel bandwidth. Hence, very fast and more powerful video compression scheme is highly desired to authenticate excellent reconstructed video quality. newlineInitially, depth map coding demonstrates vital for compression. Particularly, to keep up depth information quality and to reconstruct the depth boundary during decoding process a various approaches were analyzed. newline newline