A Deep Analysis of Similarities And Predictive Coding And Transformation Coding
Abstract
Today,information industry is developing swift and violent,people of real-time computer image information processing increasingly high demands. How to guarantee the quality of the image,taking into account real-time performance and efficiency has become a matter of concern. Thus,processing compression and disposal of the image information will be an indispensable link. Image compression is a process of the least amount of data to show as many as possible of the original image information.
traditional methods and the use of those methods in the image compression, for example estimation coding, DCT transform, data quantization, entropy coding. Estimation coding lowers the time relativity of image data. DCT transform lowers the space relativity of image data. Data quantization makes use of the redundancy of mentality and vision . Entropy coding brings down the redundancy of coding. After those process, image data will be effectively compressed.
Based on the coding technology, which includes frame and field coding mode. This paper particularly expounds the field coding of motion compensation combined with DCT transform, introduces the theory of motion compensation and the count of motion vector. Motion compensation makes better use of relativity of field data and increases the compensation ratio.
Key words :orthogonal transformation;image compression;Fast Algorithm for DCT;Matlab