CVC: The Contourlet Video Compression algorithm for real-time applications

TL;DR

This paper introduces a scalable, contourlet transform-based video compression algorithm optimized for real-time applications like video conferencing, offering high perceptual quality at low bitrates without blocking artifacts.

Contribution

It presents a novel contourlet-based scalable video coding algorithm that leverages GPU acceleration for real-time performance, improving perceptual quality over standard methods.

Findings

Performs well in compression ratio and speed.

Outperforms standard methods in perceptual quality at low bitrates.

Achieves real-time encoding and decoding using GPU acceleration.

Abstract

Nowadays, real-time video communication over the internet through video conferencing applications has become an invaluable tool in everyone's professional and personal life. This trend underlines the need for video coding algorithms that provide acceptable quality on low bitrates and can support various resolutions inside the same stream in order to cope with limitations on computational resources and network bandwidth. In this work, a novel scalable video coding algorithm based on the contourlet transform is presented. The algorithm utilizes both lossy and lossless methods in order to achieve compression. One of its most notable features is that due to the transform utilised, it does not suffer from blocking artifacts that occur with many widely adopted compression algorithms. The proposed algorithm takes advantage of the vast computational capabilities of modern GPUs, in order to achieve real-time performance and provide satisfactory encoding and decoding times at relatively low cost, making it suitable for applications like video conferencing. Experiments show that the proposed algorithm performs satisfactorily in terms of compression ratio and speed, while it outperforms standard methods in terms of perceptual quality on lower bitrates.