Machine Learning Approach to Blocking Effect Reduction in Low Bitrate Video

Abstract

This work presents an approach for blocking artifacts removal in highly compressed video sequences using an algorithm based on dictionary learning methods. In this approach only the information from the frame content is used, without any additional information from the coded bit-stream. The proposed algorithm adapts the dictionary to the spatial activity in the image, by that avoiding unnecessary blurring of regions of the image containing high spatial frequencies. The algorithms effectiveness is demonstrated using compressed video with fixed block size of 8x8 pixels.