Revised Adaptive Threshold IFS Image Compression Based on Generalized Creditability

doi:10.11834/jig.2001012250

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Revised Adaptive Threshold IFS Image Compression Based on Generalized Creditability
Vol. 6, Issue 12, Pages: 1175(2001)
Published：2001
DOI： 10.11834/jig.2001012250
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DOI：

Revised Adaptive Threshold IFS Image Compression Based on Generalized Creditability[J]. Journal of Image and Graphics, 2001, 6(12): 1175. DOI： 10.11834/jig.2001012250.

摘要

通过对分块IFS图象压缩编码过程中匹配误差的分析，提出了广义置信度的概念，并据此提出了对输入图象进行四叉树分块的自适应匹配门限（AT）算法。根据排列块的相对复杂程度，修正了自适应匹配门限的公式，提出了改进的自适应门限（RAT）IFS图象压缩编码算法。在对输入图象进行四叉树分块编码过程中，该方法可以根据当前排列块的统计特征确定匹配门限，从而使分块编码过程自动地适应输入图象。实验结果表明，这种新的编码方法可以自适应地对输入图象进行编码，且压缩比较高，有一定的实用性。

Abstract

In this paper

the MSE in IFS image compression is analyzed. The concept of generalized creditability is presented. Based on that

the algorithm of the adaptive threshold(AT) IFS image compression using quadrature partitioning structure is proposed. To improve the compression ratio of the AT algorithm while still keeping the visual performance of decoded image

the formula of the adaptive threshold is revised according to the relative complexity of each range block

which forms the revised adaptive threshold(RAT) algorithm. The methods proposed in this paper set the threshold of current range block according to its statistics character

that is

variability. Therefore

the encoding process is adaptive to the complexity of the input image. Experiments results of algorithms based on AT

RAT and fixed threshold are given in this paper as comparison. The results show that RAT algorithm can compress the input image adaptively and the compression efficiency is improved considerably. Also time consumption of each algorithm is discussed at the end of this paper.