Feature-preserving Image Compression Coding

With the rapid development of science and technology, mankind has entered the information society nowadays. The emergence and development of communication technology,data storage,distribution technology and multimedia technology make image coding techniques play a more and more important role in information processing.As the multimedia technology and network development require a higher transfer rate,and people want to use the limited space and bandwidth to store and transfer large image for a higher quality reconstructed image,therefor, image compression techniques need continuous improvement for high compression efficiency to achieve high compression rate and high-fidelity rates in the actual situation.Image compression process requires more bits to represent the image regions of interest (ROI), whereas fewer bits in other parts of the image in practical applications. Most of the information of the image is represented by the image features such as edges and textures,so extracting and maintaining a useful or retaining part of the image features for image compression becomes a new requirement in many areas.This article represents three different image compression coding algorithms with feature preserving based on the basis above.(1) The edge enhancement algorithm for image coding (IEEIC) based on WBCT. Firstly, the image is to do edge extraction by the edge detector SUSAN,and then transformed by WBCT when transform coefficients are coded by class SPIHT, lastly, the edge gets enhancement in the image decoder, which retain the edge clarity effectively. But it would produce a certain redundancy for the edge information is only used in the enhanced process.(2) The characteristics preserving for image coding algorithm (IFPIC) based on WBCT. It firstly divides the image into the edge, the texture, and the details associated with the texture, and then applies extracted edge to the transform domain to code to complete the improvements of the first algorithm. Lastly, the three parts were coded respectively to retain most of the image edge and texture information, while signal to noise ratio is also much better than the first algorithm.(3) The texture preserving for image compression algorithm (IFPIC) based on hybrid coding. Firstly, the image is also to do edge extraction by the edge detector SUSAN. It will mapped the extracted edge information to the transform domain, which is different from the above two algorithms. Then, it will take different encoding algorithms respectively according to the features of sub-band coefficients of low-frequency and high frequency after transformation. It proved that the algorithm achieved a high signal to noise ratio while retaining the vast majority of the image edge and texture information, although the speed is a little slower.