Image enhancement with histogram local minimas

K. Sumathi, S. Anitha, C. Himabindu
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引用次数: 1

Abstract

In this paper work, the author introduces local minima based image enhancement. Enhancing of images is a primary step in any advanced image processing analysis. Initially, the histogram of an unprocessed image is computed to analyze the gray level distribution of an image. Later the local minima's of histogram image is calculated. Based on these minima's the image is partitioned in to intensity based distributed images. Finally these images undergo mapping process with mean and equalization computational values. The effectiveness of proposed work is verified with PSNR (peak signal to noise ratio), entropy, AMBE (Absolute mean brightness error) & visual quality in both quantitatively, qualitatively.
用直方图局部最小值增强图像
本文介绍了基于局部最小值的图像增强方法。图像增强是任何高级图像处理分析的首要步骤。首先,计算未处理图像的直方图来分析图像的灰度分布。然后计算直方图图像的局部最小值。基于这些最小值,图像被划分为基于强度的分布式图像。最后对这些图像进行均值和均衡化计算值的映射处理。通过PSNR(峰值信噪比)、熵、AMBE(绝对平均亮度误差)和视觉质量的定量和定性验证了所提工作的有效性。
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