Implementation of P-N Learning Based Compression in Video Processing

Abstract

Now-a-days, visual information is playing a more and more important role in our daily life and effects our way of communication and living in many aspects. Digital images and video applications usually involve storage or transmission of vast amount of data. For secure transmission of data and to reduce the size of the video, video compression techniques are used. Some of the techniques that are used in present days reduce the quality, data size and the original data cannot be retrieved. To overcome these problems, P-N learning based compression technique can be used.In this work, multi-scale filter banks are used for performing necessary operations to obtain the compressed video. The image extraction from video is obtained by performing sequential frame selection method, which is converted to grayscale and then encrypted by using sparse matrix generation technique. MATLAB is a multiparadigm numerical computing environment and proprietary programming language. It allows matrix manipulations, plotting of functions and data, Implementation of algorithm, creation of user Interface. This work helps in providing security for images containing information it also helps in the reduction of bandwidth utilization since only the information contained image is transmitted instead of whole video.

Keywords: Secure transmission, Video compression, P-N learning, Multi-scale filter bank, Security, Bandwidth Utilization, Sparse matrix generation, MATLAB