变换域图像压缩算法仿真及性能分析

Simulation and analysis of image compression algorithms in transformed domains

研究了变换域压缩的基本原理与关键技术,对几种典型的变换域压缩算法进行了仿真与分析。针对同一图像采用不同的正交变换进行分解,保留相同个数的显著系数进行图像重建,以比较各种算法的稀疏表示能力,同时改变压缩比和分块大小等压缩参数,分析了各种压缩参数对算法性能的影响。实验表明,在低压缩比下,DFT具有较好的压缩效果,在高压缩比下,DCT和DWT性能优于其他算法。DWT具有时频局部化特点,因此其综合性能最佳,应用前景广泛。

Key technology and basic principle in transformed domains are analyzed,and typical compression algorithms are simulated.The same image is decomposed with different orthogonal transformations then reconstructed with the same number of significant coefficients,thus the sparse representation capability of transformation can be compared.The influence of various parameters on the performance of the algorithm is analyzed through changing compression ratio and size of blocks.The results show that DFT is more efficient under low compression ratio,while DCT and DWT are more efficient under high compression ratio.DWT has excellent comprehensive performance and broad applications for time-frequency localization.