DCTlicheng

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  研究表明，构成K一L变换矩阵的向量也就是ToePhtz矩阵的特征向量。与此同时，离散 余弦变换矩阵逼近于ToePutz矩阵的特征向量矩阵，所以离散余弦变换矩阵与自然图像的 K一L变换矩阵十分相似。经过离散余弦变换后的变换系数块的协方差矩阵Cy非常接近对角 阵，即除了对角线元素以外，其它很多元素都近似为0，并且在左上角集中了主要能量。这 反映了自然图像大部分区域变化不大，亮度突变只占少数，即图像能量以低频成分为主的特 性。通过变换后的量化，舍弃对视觉效果影响较小的次要信息，可达到进一步的压缩效果。 虽然从去相关性能的意义上讲，DCT是一种次于K一L变换的准最佳变换，但是从算法实现的角度来看，DCT则远远优于K一L变换。首先，当图像的分块大小确定后，DCT的变换矩阵也就随之确定了，不随输入信号的统计特性变化而变化 其次，二维DCT能够分解成两次一维DCT，有利于硬件实现。 (Studies have shown that constitute a K L transformation matrix vector is ToePhtz eigenvector of the matrix. At the same time, discrete The cosine transform matrix approximation in ToePutz matrix eigenvector matrix, so the discrete cosine transform matrix and natural images Is very similar to a K L transformation matrix. After discrete cosine transform, the transform coefficient block of Cy is very close to the diagonal of covariance matrix Matrix, namely except diagonal elements, many other elements are approximate to 0, and focused the main energy in the upper left corner. this Reflects the natural images most area changed little, brightness mutations accounted for only a few, the energy is given priority to with low frequency components of image Sex. Through quantitative after transformation, abandoning smaller effect on the visual performance of secondary information, can achieve further compression effect. Although from related to the performance of the sense, DCT is a kind o)