2009/11/24 by Mario Mastriani, Mastriani, Mario · 1 citation
Computer Science · #Advanced Data Compression Techniques #Blind Source Separation Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods #cs.CV
paper · pdf · doi:10.48550/arxiv.1608.00268
18 pages, 21 figures, 4 tables. arXiv admin note: substantial text overlap with arXiv:1607.03164, arXiv:1405.0632, arXiv:1608.00265
openalex publication_date 2009/11/24 · arxiv created 2016/07/31 · arxiv updated 2016/08/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.