Iteration Free Fractal Color Image Compression Using Vector Quantization

Abstract: The storage requirements for images can be excessive, if true color and a high-perceived image quality are desired. An RGB image may be viewed as a stack of three gray-scale images that when fed into the red, green and blue inputs of a color monitor, produce a color image on the screen. By convention the three images forming an RGB color image are referred to as the red, green and blue component images. The abnormal size of many images leads to long, costly, transmission times. Cost is not the only reason for speeding up transmission. The emergence of the World Wide Web has resulted in a huge increase in the exchange of image via the Internet. Image compression is method for proficiently coding digital image by minimizing the number of bits need for denoting image. It is main goal is to reduce the storage space and cut down the transmission cost and maintain good quality. The methodology used in this present work is to reduce the coding process time, intensive computation tasks and also memory requirements. The redundancies in the domain pool are reduced by the Linde Buzo Gray (LBG) Algorithm. The domain pools that are more efficient than those in the conventional fractal coding and the proposed iteration-free schemes achieve excellent performances.

Keywords: Domain Pool, Fractal Image Compression, Iteration Free Fractal Code, LBG Algorithm