Speeding up fractal image de-compression

In this paper, we propose three algorithms for fractal image decoding in which the decoding will be done in less iteration, so it would be faster. The first two algorithms are based on using an initial image which has coloration with the original image. In the first algorithm, we save the average of the original image along with the fractal codes, and we use the average image as the initial image. The second algorithm is the same as the first one except that we save the average of each domain. Then in decompression, we substitute the pixels of each range with the average of their corresponding domain, and we use this image as initial image. As the simulation results illustrate, these two algorithms especially the second algorithm accelerate decoding, but at the price of less compression ratio. In the third algorithm, we use the image resulted from a high-pass filter for finding match domains, which astoundingly provides a very high quality image at almost one iteration without any change in compression ratio.