| Summary: | 碩士 === 義守大學 === 資訊工程學系 === 101 === Fractal image compression (FIC) is a lossy compression technique based on the self-similarity of natural images and partitioned iterated function system (PIFS). It possesses the advantages of high retrieved image quality, high compression ratio, decompression speed quickly, and zoom invariant.
Image resampling can resize images to another resolution. In this thesis, adopt FIC to perform image resampling. In the decoding process, we take the image of higher resolution as the initial image to obtain super-sampled image in which the partition structure is consistent with the original image. The results are compared with other common image resizing methods.
Based on sparse presentation of signals, compressed sensing (CS) uses a few sampling signal to retrieve the original signal via some solving algorithm. In this thesis, we use orthogonal matching pursuit (OMP) and LS-OMP to implement FIC. In encoder, we add one more contrast adjustment term to fractal code. The proposed method increases the image quality. The results are compared with the traditional fractal image compression.
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