An Efficient Compression Technique for Color Images

With the access of the information age the need for mass information storage and rapid communication links grows. Storing images in less memory leads to a direct reduction in storage cost and faster data transmissions. These facts justify the efforts, for development of new image compression algorithms. Research regarding is to improve the execution of Fractal image compression as far as accelerating the encoding process and increasing the compression ratio while keeping a high reconstructed image quality.

This paper proposes an Fractal image compression (FIC) method for Color images fetched out for variable block size. The image here is partitioned in to block by considering maximum and minimum size of the range. The proposed method divides color image into three RGB planes and employs fractal transformation with entropy coding. By applying the inverse transforms and iterative functions, the image is reconstructed at end. The outcomes of the planned method shows improvement in fractal compression scheme applied to both color and gray scale images. Here high CR and PSNR values are acquired compared to fixed range block size of 4 by 4 iterations and other subsisting methods. This algorithm achieves a compression ratio of up to 20 with a peak signal to noise ratio (PSNR) as high as 30dB.