Union is strength in lossy image compression
This work addresses image compression quality for applications like storage and transmission, but it appears incremental as it compares and combines existing methods without introducing new ones.
The paper compared various image compression techniques, including wavelets and Karhunen-Loeve Transform, applied alone or combined, finding that combined versions achieved lower Mean Squared Error and higher Peak Signal to Noise Ratio for better image quality, even with noise.
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.