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Image coding based on fractal approximation and vector quantization

机译:基于分形逼近和矢量量化的图像编码

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We propose a coding algorithm for still images using fractal approximation and vector quantization (VQ). The conventional fractal coding algorithms indirectly used the gray patterns of an original image with contraction mapping, whereas the proposed fractal coding method employs a previously approximated image as a domain pool and uses its gray patterns. Thus, the proposed algorithm employs fractal approximation without the constraint of contraction mapping. To approximate an original image, we use an orthogonal polynomial transform and to encode the transform coefficients we employ VQ. Also, for variable block-size segmentation, we use the fractal dimension that represents the similarity of regions in a block and the roughness of the gray surface of a region. Computer simulations with several test images show that the proposed method shows better performance than the conventional fractal coding methods for encoding still pictures.
机译:我们提出了一种使用分形近似和矢量量化(VQ)的静止图像的编码算法。传统的分形编码算法间接使用具有收缩映射的原始图像的灰度图案,而所提出的分形编码方法采用先前近似的图像作为域池,并使用其灰度模式。因此,所提出的算法在没有收缩映射的约束的情况下使用分形近似。为了近似原始图像,我们使用正交多项式变换并对我们采用VQ的变换系数进行编码。此外,对于可变块尺寸的分割,我们使用表示块中区域的相似性的分形尺寸和区域的灰度表面的粗糙度。具有多个测试图像的计算机模拟表明,该方法显示出比传统的分形编码方法更好的性能,用于编码静止图像。

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