%0 Journal Article
%T A Novel Optimized Golomb-Rice Technique for the Reconstruction in Lossless Compression of Digital Images
%A Shaik. Mahaboob Basha
%A B. C. Jinaga
%J ISRN Signal Processing
%D 2013
%R 10.1155/2013/539759
%X The research trends that are available in the area of image compression for various imaging applications are not adequate for some of the applications. These applications require good visual quality in processing. In general the tradeoff between compression efficiency and picture quality is the most important parameter to validate the work. The existing algorithms for still image compression were developed by considering the compression efficiency parameter by giving least importance to the visual quality in processing. Hence, we proposed a novel lossless image compression algorithm based on Golomb-Rice coding which was efficiently suited for various types of digital images. Thus, in this work, we specifically address the following problem that is to maintain the compression ratio for better visual quality in the reconstruction and considerable gain in the values of peak signal-to-noise ratios (PSNR). We considered medical images, satellite extracted images, and natural images for the inspection and proposed a novel technique to increase the visual quality of the reconstructed image. 1. Introduction Digital images have become very common in the present societal needs, especially in the electronic industry and other applications like medical imaging, satellite imaging, multimedia applications, and high-speed data internet data paths. The concept of image processing thus leads to the evolution of different image acquisition devices like still and video cameras and web cameras. Thus, our work is to designate a novel technique for solving the forward as well as inverse problems in the still image compression. The solutions derived from these forward and inverse matrix computations facilitated a comprehensive meaning for the image compression for JPEG 2000 and JPEG-LS [1¨C3]. 2. Review of Existing Techniques JPEG 2000 still image compression standard supports both lossy and lossless compression schemes, whereas JPEG-LS is a lossless image compression scheme. The JPEG-LS uses statistical based coding techniques such as Golomb, Huffman coding, and Golomb-Rice (GR) coding techniques. Nowadays most of the VLSI-based companies and multimedia application oriented industries are offering the Golomb and Golomb-Rice coding for their applications. Thus, it is observed from the literature survey that the necessity of optimization is an essential parameter in image compression. Somasundaram and Sumithra [4] derived a compression algorithm using the GC technique. In their research work it was shown that the results were compared with existing coding techniques along with
%U http://www.hindawi.com/journals/isrn.signal.processing/2013/539759/