一种有效压缩平滑图像的混合模型

J. Mayer
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引用次数: 2

摘要

提出了一种新的有损图像压缩方法,将图像表示为由可变大小的直角三角形组成的片段。所提出的递归三角分区比平方分区更有效。采用一种新颖而经济的混合模型(类似于贝塞尔多项式)来表示每个三角形表面。提出了一个三角形区域混合曲面的设计框架。这个经济模型允许系数(控制点)在相邻三角形之间共享。与基于块的技术相比,共享可以减少块。该技术对平滑过渡的图像特别有吸引力。压缩和视觉质量的结果与使用分解成七个波段的小波编解码器比较有利。为了进一步降低控制点比特流的熵,提出了一种基于优先级队列的贪心算法。与控制点的均匀量化相比,该优化步骤在率失真R-D意义上实现了更好的性能。
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A blending model for efficient compression of smooth images
The proposed novel lossy image compression approach represents an image as segments comprised of variable-sized right-angled triangles. The recursive triangular partitioning proposed is shown to be more efficient than square partitioning. A novel and economic blending model (similar to Bezier polynomials) is applied to represent each triangular surface. A framework to design blending surfaces for triangular regions is presented. This economic model allows coefficient (control point) sharing among neighbor triangles. Sharing results in blockiness reduction as compared to block-based techniques. The technique is specially appealing to images with smooth transitions. Compression and visual quality results compare favorably against a wavelet codec using decomposition into seven bands. As an alternative, a greedy algorithm based on priority queues is proposed to further reduce the entropy of the control point bitstream. This optimization step achieves better performance in a rate-distortion R-D sense when compared to uniform quantization of the control points.
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