A New Method of Neural Network Based Fast Fractal Image Compression
Keywords:
Contractive transform, domain classification and feature vector, Partial discharge image, pattern recognition, fractal image compressionAbstract
Fractal compression is a lossless 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 such as encoding and global search. Many different researchers and companies are trying to develop a new algorithm to achieve shorter encoding times and smaller file sizes. However, 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 applications. The primary objective of this paper is to investigate the comprehensive coverage of the principles and techniques of fractal image compression. The experimental results show that the application of the designed hybrid image compression method can increase the signal-to-noise ratio of an image while guaranteeing a high compression ratio.
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