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首页> 外文期刊>WSEAS Transactions on Signal Processing >Image Enhancement with Minimum Mean Brightness Error Via Automatic Histogram Dividing
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Image Enhancement with Minimum Mean Brightness Error Via Automatic Histogram Dividing

机译：通过自动直方图划分实现最小平均亮度误差的图像增强

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摘要

Mean separated histogram equalization in order to preserve the original mean brightness has been proposed. To provide the minimum mean brightness error after the histogram modification, the input image's histogram is successively divided by the factor of 2 until the mean brightness error is satisfied the defined threshold. Then each divided group or sub-histogram will be independently equalized based on the proportional input mean. To provide the overall minimum mean brightness error, each group will be controlled by adding some certain pixels from the adjacent grey level of the next group for giving its mean near by the corresponding the divided mean. However, it still exists some little error which will be put into the next adjacent group. By successive dividing the original histogram, we found that the absolute mean brightness error is gradually decreased when the number of group is increased. Therefore, the error threshold is assigned in order to automatically dividing the original histogram for obtaining the desired absolute mean brightness error (AMBE). This process will be applied to the color image by treating each color independently.
机译：为了保持原始的平均亮度，已经提出了均值分离直方图均衡化。为了在直方图修改后提供最小的平均亮度误差，将输入图像的直方图相继除以2，直到平均亮度误差满足定义的阈值。然后，将基于比例输入平均值独立地均衡每个划分的组或子直方图。为了提供整体的最小平均亮度误差，将通过从下一组的相邻灰度级中添加一些特定像素来控制每组，以通过相应的划分后的平均值来给出其平均值附近。但是，它仍然存在一些小错误，将被放入下一个相邻组。通过连续分割原始直方图，我们发现，当组数增加时，绝对平均亮度误差将逐渐减小。因此，分配误差阈值是为了自动划分原始直方图以获得所需的绝对平均亮度误差（AMBE）。通过独立处理每种颜色，此过程将应用于彩色图像。

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