Set Partitioning Embedded Block Coder Algorithm

Abstract

Present analysis focuses to design of efficient compression of multidimensional, multispectral and volumetric digital images. The digital representation of images and videos allows processing and archiving tasks to be integrated in multimedia platforms, computing and communications. The efficient representation of visual information is at the centre of image compression systems. The efficiency of a representation refers to the capture of significant information about an object of interest in a smaller description. Image compression techniques have numerous applications in the field of multimedia broadcasting channels, video conferencing, medical imaging and neural networks.  An increasing demand for multimedia content such as digital images and video has led to great interest in research into compression techniques. The development of higher quality and less expensive image acquisition devices has produced steady increases in both image size and resolution, and a greater consequent for the design of efficient compression systems. Although storage capacity and transfer bandwidth has grown accordingly in recent years, many applications still require compression. In general, present paper investigates still image compression in the transform domain. The main objective is to design a compression system suitable for processing, storage and transmission, as well as providing acceptable computational complexity suitable for practical implementation. The basic rule of compression is to reduce the numbers of bits needed to represent an image. SPECK use sets in the form of blocks of contiguous coefficients to exploit similarities within the sub bands, whereas the SPIHT algorithm uses spatial trees which span and exploit the similarity across different sub bands of wavelet decomposition. SPECK comprises of three stages initialization, sorting, and refinement, and uses two linked lists: list of insignificant sets (LIS) and list of significant pixels (LSP).