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Modified Dynamic Histogram Equalization For Image Enhancement in Gray-scale Images

机译:灰度图像中图像增强的修改动态直方图均衡

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To improve the quality of digital images captured in low light environment from consumer electronics devices like cell phone cameras, Modified Dynamic Histogram Equalization (MDHE) is proposed. Initially, the proposed method divides the histogram into two sub-histograms based on median. Then 2nd subhistogram is further divided into two sub-histograms based on median of it. The resultant sub-histograms are clipped according to the mean of the intensity occurrence of the input image independently. The new dynamic range is allocated to each sub-histogram. The first sub-histogram is equalized independently using Global Histogram Equalization (GHE) method. GHE is found the better enhancement for lower gray-levels and suffers over-enhancement problem in higher gray-level. The proposed method utilizes the advantages of both GHE and QDHE. This method utilizes GHE for enhancing lower gray-levels and QDHE for enhancing higher gray-levels. Simulation results show that the proposed method yields better quality images in terms of Discrete Entropy value compared with other conventional methods.
机译:为了提高从客户手机相机等消费电子设备中捕获的低光环境中捕获的数字图像的质量,提出了修改的动态直方图均衡(MDHE)。最初,所提出的方法将直方图分成基于中位数的两个子直方图。然后,2 nd 亚末端图进一步分为基于它的中位数的子直方图。根据输入图像的强度发生的平均值剪裁所得到的子直方图。新的动态范围被分配给每个子直方图。使用全局直方图均衡(GHE)方法独立地均衡第一子直方图。在较高的灰度级别中发现了更好的增强,较低的灰度水平,遭受过度增强问题。该方法利用GHE和QDHE的优点。该方法利用GHE增强较低的灰度级和QDHE,以增强更高的灰度级别。仿真结果表明,与其他常规方法相比,该方法在离散熵值方面产生更好的质量图像。

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