The approximation of two-dimensional highly correlated grey value functions can be performed using a linear model of the type f(x, y)=a+bx+cy. The set of plane parameters (PPs) (a, b, c) can be determined in the least squares sense for a block of size N*N pixels, for example. Starting with a block size of 2*2 pixels, it is shown that the PPs obey a recursive law such that the PPs of a 2N*2N block can be computed recursively when only the PPs of the four adjacent subblocks of size N*N in the lower decomposition level are known. This concept of recursive plane decomposition (RPD) is embedded in a quadtree data structure to obtain a new variable block size image coding algorithm that offers a high performance at a low computational cost. Extensive comparisons to other state-of-the-art image coding algorithms are reported.
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机译:可以使用类型为f(x,y)= a + bx + cy的线性模型执行二维高度相关的灰度值函数的逼近。例如,可以针对大小为N * N像素的块,在最小二乘方的意义上确定一组平面参数(PPs)(a,b,c)。从2×2像素的块大小开始,示出了PP遵循递归定律,使得当仅N×N个大小的四个相邻子块的PP中的2N×2N块的PP可以被递归计算时。较低的分解度是已知的。递归平面分解(RPD)的概念被嵌入到四叉树数据结构中,以获得一种新的可变块大小图像编码算法,该算法以较低的计算成本提供了高性能。报告了与其他最新图像编码算法的广泛比较。
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