A new method of neural network based fast fractal image compression
AbstractFractal compression is a loss compression method for digital images, based on fractals. The 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. Fractal Image Compression (FIC) techniques take more time to perform processes are encoding and global search. Many different researchers and companies are trying to develop a new algorithm to reach shorter encoding time and smaller files. But there are still some problems with fractal compression. Fractal image compression is promising both theoretically and practically. The encoding speed of the traditional full search method is a key factor rendering the fractal image compression unsuitable for real-time application. The primary objective of this paper is to investigate the comprehensive coverage of the principles and techniques of fractal image compression. The experimental result shows that the application of the designed hybrid image compression method can increase the signal-to-noise ratio of an image while the high compression ratio of the image is guaranteed.
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