Fast Fractal Image Compression using Statistical Self-Similarities Mechanism

Fractal image compression is a technique used for encoding images compactly based on fractals. This method is best suited for textures and natural images, relying on the fact that parts of an image often resemble other parts of the same image. But fractal Image compression (FIC) consumes most of the time during encoding to find the best matching pair of range-domain blocks. Different techniques have been analyzed to reach shorter encoding time. This paper proposes a mechanism of Statistical Self-Similarity to achieve image compression. Unlike the other approaches no need of two partitions of same image into range and domain blocks. Instead a single partition can serve. The Statistical Self-Similarity is based on the mean value found among various blocks of subsets. The overhead of Image is halved. This makes the approach faster than other traditional approaches.