Wavelet and Curvelet Based Image Compression with Dead Zone Quantization

An image file contains huge amounts of information that requires high storage space, large transmission bandwidths and long transmission times. So it is useful to compress the image by storing only the required information to reconstruct the original image. An image can be considered as a matrix of pixel or intensity values. In order to compress an image redundancies must be evaluated, for example, several areas where there is small change or there is no change among pixel values Hariom Yadav & Hitesh Gupta (2013). So the images having the consistent color with larger areas will have large redundancies, and on the other hand an image having more changes in color by means of less redundant becomes more difficult to compress.