An accelerated method to predict the quality of decoded images in fractal image coding

Qiang Wang, Sheng Bi, Guohua Jin
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Abstract

With many observations, we find that there exists a logarithmic relationship between the average collage error (ACER) and the quality of decoded images. By making use of the ACER in the encoding process, the quality of decoded images can be predicted without fractal decoding. In order to shorten the prediction process further, an accelerated version of the prediction method is proposed. By theoretical derivations and analyses, a low limit of accumulated collage error (LLPACE) is introduced which provides an effective way to evaluate the percentage of total collage error accounted by the accumulated collage error (ACE). Experiments show that for either basic fractal coding or other three fast fractal coding methods, the accelerated prediction method can provide satisfying performance and reduce about one third of total computations in the encoding process.
分形图像编码中一种快速预测解码图像质量的方法
通过大量的观察,我们发现平均拼贴误差(ACER)与解码图像质量之间存在对数关系。在编码过程中利用ACER,无需分形解码即可预测解码图像的质量。为了进一步缩短预测过程,提出了一种加速版的预测方法。通过理论推导和分析,引入了累积拼贴误差下限(LLPACE),为评估累积拼贴误差占总拼贴误差的百分比提供了一种有效的方法。实验表明,无论对基本分形编码还是其他三种快速分形编码方法,加速预测方法都能提供令人满意的编码性能,并将编码过程中的总计算量减少约三分之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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