Modeling using 2-D areas of ideal cross-point regions for lossless images compression

Abstract

This paper presents a new scheme using 2-D areas of ideal cross-point regions which are a new part in the theory of cross-point regions. When using cross-point regions we need to determine the rule of building cross-point maps, this takes a long time and a big space for storing these maps, this also brings about not high compression ratio when using one dimensional cross-point regions because many coordinates of data points need to be saved for decoding. When these 2-D areas with new features are used, the scheme of 2-DICRIC (2-D Ideal Cross-point Regions for lossless Image Compression) for losslessly encoding and decoding images is used to get higher compression ratio. The base idea of this method is the effect of Gray coding on cross points. Before Gray coding, data sets of cross points are determined, they are called the ideal cross point regions (ICRs). After Gray coding, these regions always eoHtaãt cBily 1 bits or 0 bits depending on the number of bit plane after the operation of bit plane decomposition. With the characteristic of images, grey values do not change much in a specific area, especially in medical images which have many regions with the approximate grey levels, the theory with these 2-D areas has important effects on the compression ratio when encoding and decoding processes of lossless image compression for data transmission are proceeded. The scheme can be applied for lossless images compression and cryptography.