Fast Cosine Transform to increase speed-up and efficiency of Karhunen-Loeve Transform for lossy image compression
This work addresses image compression efficiency for applications like storage and transmission, but it appears incremental as it builds on existing transforms with a new combination.
The paper tackled improving lossy image compression by combining Fast Cosine Transform with Karhunen-Loeve Transform, resulting in a technique that outperformed JPEG and JPEG2000 with lower MAE and MSE, higher PSNR, and better image quality.
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.