Still image coding based on vector quantization and fractal approximation
Still image coding based on vector quantization and fractal approximation
复制标题
DOI：
10.1109/83.491335
复制
发表时间：
1996-04
期刊：
影响因子：
--
通讯作者：
I. K. Kim;Rae-Hong Park
中科院分区：
文献类型：
--
作者：
I. K. Kim;Rae-Hong Park
本文提出了一种基于矢量量化（VQ）和分形逼近的静止图像编码算法，该算法对输入图像的低频分量进行矢量量化，对残差进行分形映射编码。传统的分形编码算法通过压缩映射间接地利用原始图像的灰度模式，而本文提出的分形编码方法则是将一幅经过近似抽取的图像作为一个域池，利用其灰度模式进行编码。因此，该算法利用分形近似没有压缩映射的约束。对于原始图像的近似，我们采用离散余弦变换（DCT），而不是传统的基于多项式的变换。此外，对于可变块大小分割，我们使用块的分形维数表示区域的灰度表面的粗糙度。对几幅测试图像的计算机模拟表明，该方法在静态图像的编码中表现出比传统分形编码方法更好的性能。
In this paper, we propose a coding algorithm for still images using vector quantization (VQ) and fractal approximation, in which low-frequency components of an input image are approximated by VQ, and its residual is coded by fractal mapping. The conventional fractal coding algorithms indirectly used the gray patterns of an original image with contraction mapping, whereas the proposed fractal coding method employs an approximated and then decimated image as a domain pool and uses its gray patterns. Thus, the proposed algorithm utilizes fractal approximation without the constraint of contraction mapping. For approximation of an original image, we employ the discrete cosine transform (DCT) rather than conventional polynomial-based transforms. In addition, for variable blocksize segmentation, we use the fractal dimension of a block that represents 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.