Designing and Implementation of Efficient Fuzzy Logic Based Fractal Image Compression Technique in DCT Domain Using Quadtree Algorithm

Fractal image compression (FIC) is an image coding Technology based on the local similarity of image structure. It is broadly used in many fields such as image recovery, image denoising, image verification, and encryption. FIC, still, bear the high computational complexity in encoding. Although many schemes are available to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper a new novel approach for efficient fuzzy logic based fractal image compression in DCT domain using quadtree algorithm is proposed. This paper deals with the fuzzy logic based method because, fuzzy logic is a strong tool to handle vagueness, and since images are vague in terms of pixel values fuzzy logic is most appropriate logic for its analysis. In the proposed technique one domain block is considered for each range block and searched only for matched contrast scaling. Hence the outcomes fractal code does not contain coordinates of the matched domain block. This leads the advantage that the Quadtree algorithm can be here applied and the size of range block can be reduce as small as 2x2 pixels. Hence the quality of decoded image can be improved while the compression ratio can be maintained. The advantage of using fuzzy based technique is that, Fuzzification of an image leads to the reduction in the contrast and brightness of input image to be compressed. The advantage of this reduction in contrast and brightness is that this reduction leads to increase the pixel redundancy and hence help to increase the compression ratio (CR) and peak signal to noise ratio (PSNR) during the image compression. The results obtained after implementation of the proposed fractal image compression technique shows that the encoding time required is very small as compare to conventional fractal image compression (CFIC) techniques. Moreover the PSNR and compression values obtained from proposed work are higher than CFIC.