High-Performance Compression of Visual InformationA Tutorial Review Part I: Still PicturesOLIVIER EGGER, PASCAL FLEURY, TOURADJ EBRAHIMI,ANDMURAT KUNT,FELLOW, IEEEDigital 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 the problem of image compression in the last two decades. Two different compression categories must be distinguished: lossless and lossy. Lossless compression is achieved if no distortion is introduced in the coded image. Applications requiring this type of compression include medical imaging and satellite photography. For applications such as video telephony or 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 are overviewed. Part I covers still image coding, and Part II covers motion picture sequences.In this first part, still image coding schemes have been classified into predictive, block transform, and multiresolution approaches. Predictive methods 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 functionalities of the image coding schemes. For that purpose, second-generation coding techniques segment the image into semantically meaningful parts. Therefore, parts of these methods have been adapted to work for arbitrarily shaped regions. In order to add another functionality, such as progressivetransmission of the information, specific quantization algorithmsmust be defined. A final step in the compression scheme is achieved by the codeword assignment. Finally, coding results are presented which compare state- of-the-art techniques for lossy and lossless compression. The different artifacts of each technique are highlighted and discussed. Also, the possibility of progressive transmission is illustrated.Keywords Compression, image processing, JPEG, MPEG, standards, still pictures.Manuscript received July 24, 1997; revised March 12, 1999. O. Egger is with Oasya S.A., 1110 Morges, Switzerland. P. Fleury, T. Ebrahimi, and M. Kunt are with the Signal Process- ing Laboratory, Swiss Federal Institute of Technology, 1015 Lausanne, Switzerland.Publisher Item Identifier S 0018-9219(99)04156-0.I.INTRODUCTION Every digital image acquisition system produces pictures in its canonical form. This means that the analog scene is sampled in space and quantized in brightness. If the sampling step size is small enough, the integration ability of the human visual system will give the illusion of a continuous picture to the human observer. In that sense, a digital image is anarray of integer numbers. However, this canonical form needs a large number of bits for its representation. For example, a 256256 picture using 8 bits per pixel needs half a million bits for its representation. The information contained in a sequence of images for video is even higher due to the additional temporal dimension. Image data compression aims at minimizing the number of bits required to represent an image. Data compression has wide areas of applications. Video telephony between two speakers or teleconferencing on two PCs via the normal twisted-pair phone lines is only possible with very low bit rate compression systems. Nearly all multimedia applications, such as interactive databases (encyclopedias, electronic newspaper, travel information, and so on), need a strong compression of the huge input data consisting of text, audio, and visual information. Other applications can be found in remote sensing, education, and entertainment. Some applications allow for visible distortions of the in- put images in exchange for high compression ratios. This is typically the case for applications such as teleconferencing or accessing images from a distant server (for example, applications related to the World Wide Web). Such coding schemes are called lossy. In other applications, however, no distortion of the input image is tolerated. Compression of medical images is a typical example of this category. Coding schemes that introduce no distortion are termed lossless. In the past, most of the effort has been dedicated to im- proving the compression ratios of the compression scheme itself. Functionalities of the compression schemes were considered less important. Second-generation image coding techniques 1 attempt to split an image into visual prim-00189219/99$10.00 1999 IEEE976PROCEEDINGS OF THE IEEE, VOL. 87, NO. 6, JUNE 1