High-performance compression of visual information - A tutorial review - Part I: Still pictures

Digital images have become an important source of information in the modern world of communication systems. In their raw form, digital images require a tremendous amount of memory. Many research efforts have been devoted to t he problem of image compression in the last two decades. Two different comp ression categories must be distinguished: lossless and lossy. Lossless comp ression is achieved if no distortion is introduced in the coded image. Appl ications requiring this type of compression include medical imaging and sat ellite photography. For applications such as video telephony ol multimedia applications, some loss of information is usually tolerated in exchange for a high compression ratio. In this two-part paper, the major building blocks of image coding schemes a re overviewed. Part I covets still image coding, and Parr II covers motion picture sequences. In this first part, still image coding schemes have been classified into pr edictive, block transform, and multiresolution approaches. Predictive metho ds are suited to lossless and low-compression applications. Transform-based coding schemes achieve higher compression ratios for lossy compression but suffer from blocking artifacts at high-compression ratios. Multiresolution approaches are suited for lossy as well for lossless compression. At lossy high-compression ratios, the typical artifact visible in the reconstructed images is the ringing effect. New applications in a multimedia environment drove the need for new functio nalities of the image coding schemes. For that purpose, second-generation c oding techniques segment the image into semantically meaningful parts. Ther efore, parts of these methods have been adapted to work for arbitrarily sha ped regions. In ol-der to add another functionality, such as progressive tr ansmission of the information, specific quantization algorithms must be def ined. A final step in the compression scheme is achieved by the codeword as signment. Finally, coding results ale presented which compare state-of-the-art techni ques for lossy and lossless compression. The different artifacts of each te chnique ale highlighted and discussed. Also, the possibility of progressive transmission is illustrated.