Image Compression: A Survey <s> Low <s> A computationally efficient image compression technique is presented, which is based on visual patterns as well as least squares fractal approximation by a self-affine system (SAS). Simulation studies demonstrate that the use of visual pattern-based technique can code the shade (flat) regions of an image more efficiently than fractal techniques. Furthermore, the proposed technique not only gives an encoding speed several times faster than other SAS-based fractal coding techniques but also achieves higher compression ratios and better fidelity. <s> BIB001 </s> Image Compression: A Survey <s> Low <s> Fractal image encoding is a computationally intensive method of compression due to its need to find the best match between image subblocks by repeatedly searching a large virtual codebook constructed from the image under compression. One of the most innovative and promising approaches to speed up the encoding is to convert the range-domain block matching problem to a nearest neighbor search problem. This paper presents an improved formulation of approximate nearest neighbor search based on orthogonal projection and pre-quantization of the fractal transform parameters. Furthermore, an optimal adaptive scheme is derived for the approximate search parameter to further enhance the performance of the new algorithm. Experimental results showed that our new technique is able to improve both the fidelity and compression ratio, while significantly reduce memory requirement and encoding time. <s> BIB002
complexity fractal-based compression: Technique based on human visual system is the method using a simple and competent 4×4 blocks is divided into perceptually shade and edge blocks. For each edge block instead of using MMSE criterion from small domain pool with respect to every 52 edge patterns Firstly it finds Same domain block using properties like mean, range, location and orientation. By guessing mean intensity correlation found in the neighborhood of a shade block can be easily decreases  . Shade region of image suitably can code by Pattern based technique is proved by simulation. Table 1 shows some Fractal Image Compression Techniques. Proposed Scheme not only is better in term of encoding speed and compression ratios BIB001 . Region are coded corresponding to segmentation map computed already that explicit region based functionalities images BIB002 . Compression using genetic algorithm: Performance of the fractal based on GA comprises of 3 components total amount of search space points second number of cycles T and initial population size S. Iterations will varies from image to image for sake of near-optimal solution. Image self transformability characteristic is take into account and also reduced. Compression implements the GAs which greatly decreases the search space. It discusses practical implementation of the proposed method and classification technique  .