Union is strength in lossy image compression

TL;DR

This paper compares various image compression techniques, demonstrating that combined methods yield superior image quality with lower error metrics, even amidst noise.

Contribution

It introduces a comparative analysis of multiple compression techniques and shows that their combination enhances image quality over individual methods.

Findings

Combined compression techniques outperform individual methods in quality.

Simulations show lower MSE and higher PSNR with combined methods.

Combined methods maintain better quality even with noise presence.

Abstract

In this work, we present a comparison between different techniques of image compression. First, the image is divided in blocks which are organized according to a certain scan. Later, several compression techniques are applied, combined or alone. Such techniques are: wavelets (Haar's basis), Karhunen-Loeve Transform, etc. Simulations show that the combined versions are the best, with minor Mean Squared Error (MSE), and higher Peak Signal to Noise Ratio (PSNR) and better image quality, even in the presence of noise.