二维匹配跟踪自适应图像编码
Adaptive Image Coding Based on Matching Pursuit
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摘要: 提出一种基于二维可分离Gabor函数时频原子字典的自适应图像编码方法.该方法能够产生嵌入式、渐进PSNR的位流,并具有对感兴趣区域ROI优先编码的能力.它将原始图像表示成若干时频原子函数的线性叠加,这些时频原子取自冗余的时频原子字典,可以最佳匹配图像中所包含的各种结构特征.实验结果表明,该算法能够有效地捕捉图像中所包含的纹理和边缘等具有高频窄带的信号特征,在极低位率下该算法的图像恢复质量要优于零树SPIHT编码算法.Abstract: A new image coding method is proposed that can produce an embedded and progressive-PSNR bit stream with region of interest ability. It represents the original image as linear composition of some time-frequency atoms. These atoms are extracted from a redundant dictionary to match the time-frequency characteristics of original image in a great degree. Our experiments show that it can capture texture and edge characteristics efficiently and the quality of recovered image is better than SPIHT at low bit rates.
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