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Method for adaptive quantization by multiplication of luminance pixel blocks by a modified, frequency ordered hadamard matrix

机译:通过将亮度像素块乘以修改的频率有序哈达玛德矩阵进行自适应量化的方法

摘要

A method for spatial compression of a digital video picture to obtain the quantizer step size so as to avoid over "lossy" reconstruction and loss of detail. The first step is dividing the picture into a plurality of macroblocks, for example, 16×16 macroblocks, each macroblock having luminance or chrominance pixel blocks, for example four 8×8 pixel blocks. This is followed by multiplying each luminance pixel block by a modified frequency ordered Hadamard matrix to yield a first dimension of each luminance pixel block. The first dimension of each pixel block is then multiplied by the inverse of the modified frequency ordered Hadamard matrix to yield a second dimension of each luminance pixel block. The second dimension of the pixel luminance block is then weighted against a weight matrix, and the individual weighted terms are summed for each pixel block. The minimum of the weighted terms is selected. This minimum is used to detect the edge or texture of the macroblock, e.g., for setting the quantizer step size.
机译:一种用于数字视频图片的空间压缩以获得量化器步长的方法,以避免过度的“有损”重建和细节损失。第一步是将图片划分为多个宏块,例如16×16宏块,每个宏块都具有亮度或色度像素块,例如四个8×8像素块。接下来,将每个亮度像素块乘以修改的频率排序的哈达玛矩阵,以产生每个亮度像素块的第一维。然后,将每个像素块的第一维度乘以修改后的频率有序哈达玛矩阵的逆,以得出每个亮度像素块的第二维度。然后,针对权重矩阵对像素亮度块的第二维进行加权,并对每个像素块求和各个加权项。选择最小的加权项。该最小值用于检测宏块的边缘或纹理,例如,用于设置量化器步长。

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