基于演化算法的卷曲DCT图像压缩

Warped DCT image compression based on evolutionary algorithm

卷曲离散余弦变换(WDCT)利用频率卷曲原理解决了离散余弦变换(DCT)模糊物体边缘的缺陷,但传统方法在选取WDCT频率卷曲参数时存在较大的难度。通过利用演化算法全局寻优的特点选取WDCT的频率卷曲参数,提出一种基于演化算法的WDCT图像压缩新算法(EAWDCT)。该算法针对频率卷曲参数特征,采用启发式方法设计染色体编码方式及演化算子,以加快收敛速度,最终达到快速准确的找到最优频率卷曲参数。实验结果表明,利用新的EAWDCT算法生成的WDCT矩阵能有效提高峰值信噪比、信噪比并减少均方根误差。

In the process of image compression, the discrete cosine transform （DCT） makes the image blurry. With the frequency warping, the warped discrete cosine transform （WDCT） overcomes this shortcoming. However, it is difficult for traditional algorithms to select the frequency warping parameters. Therefore, in this paper, we present a new WDCT image compression algorithm based on an evolutionary algorithm （EAWDCT） to select the parameters with the global optimization of the evolutionary algorithm. To improve the convergence speed and to gain the best parameters quickly and accurately, a heuristic method is used to design the chromosome coding methods and evolutionary operators according to the parameters characteristics. The experiments show that the new algorithm （EAWDCT） improves the peak signal to noise ratio and signal to noise ratio while reducing the root-mean-square error effectively.