INTEGER TO INTEGER MULTIWAVELETS FOR LOSSLESS IMAGE-COMPRESSION

In computer science and information theory, image compression is the process of encoding information using fewer bits than the original representation would use. Compression is useful because it helps reduce the consumption of expensive resources, such as hard disk space or transmission bandwidth. Image compression may be lossless or lossey. Lossless image compression is. a class of image-copression algorithms that allows the exact original-data to be reconstructed from the compressed data: The term lossless is in contrast to lossy image compression, which only allows an approximation of the original data to be reconstructed, in exchange for better compression rates. Lossless compression is preferred for archival purposes and often for medical imaging, satellite imaging, or technical drawings. For the urgent requirement of efficient lossless compression and high fidelity compression, more and more research of lossless image compression will be concerned. After the introduction of the lifting scheme and the integer to integer multiwavelets, we present the approach to build integer to integer multiwavelets. In addition, experimental results of applying these multiwavelets to lossless image compression are presented.