Fast Cosine Transform to increase speed-up and efficiency of Karhunen-Loeve Transform for lossy image compression

TL;DR

This paper introduces a combined approach using Fast Cosine Transform and Karhunen-Loeve Transform for lossy image compression, demonstrating superior performance over JPEG and JPEG2000 in quality metrics.

Contribution

The paper proposes a novel combined technique utilizing Fast Cosine Transform with Karhunen-Loeve Transform, enhancing compression efficiency and image quality.

Findings

Combined method achieves lower MAE and MSE

Higher PSNR indicates better image quality

Outperforms JPEG and JPEG2000 in tests

Abstract

In this work, we present a comparison between two techniques of image compression. In the first case, the image is divided in blocks which are collected according to zig-zag scan. In the second one, we apply the Fast Cosine Transform to the image, and then the transformed image is divided in blocks which are collected according to zig-zag scan too. Later, in both cases, the Karhunen-Loeve transform is applied to mentioned blocks. On the other hand, we present three new metrics based on eigenvalues for a better comparative evaluation of the techniques. Simulations show that the combined version is the best, with minor Mean Absolute Error (MAE) and Mean Squared Error (MSE), higher Peak Signal to Noise Ratio (PSNR) and better image quality. Finally, new technique was far superior to JPEG and JPEG2000.