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Rate-Distortion Optimized Tree-Structured Compression Algorithms for Piecewise Polynomial Images

机译:分段多项式图像的速率失真优化树结构压缩算法

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摘要

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymp- totic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D be- havior (D(R) ~ C02^-c1 R), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of 0(NlogN). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of 0(NlogN). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.
机译:本文提出了一种基于树结构分割的新颖编码算法,该算法通过使用基于R-D的修剪和连接方案,对称为一类多项式的简单信号实现了正确的渐近率失真(R-D)行为。对于一维情况,我们的方案基于信号的二叉树分割。该方案使用多项式模型近似信号段,并在不同信号段之间利用R-D最佳位分配策略。该方案进一步联合编码相似的邻居,以实现正确的指数衰减R-D行为(D(R)〜C02 ^ -c1 R),从而比经典的小波方案有所改进。我们还证明了该方案的计算复杂度为0(NlogN)。然后,我们使用四叉树显示该方案在二维情况下的扩展。对于由白色多边形对象在均匀的黑色背景下组成的多边形图像模型,该四叉树编码方案还实现了指数衰减的R-D行为,其计算成本为0(NlogN)。同样,关键是R-D优化的修剪和加入策略。最后,我们用数值结果得出结论,这些结果表明,对于像摄影师这样的真实图像,所提出的四叉树编码方案在0.15 bpp左右的低速率下,比JPEG2000的性能高出约1 dB。

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