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An Effective Local Contrast Enhancement Technique by Blending of Local Statistics and Genetic Algorithm

机译:融合局部统计和遗传算法的有效局部对比度增强技术。

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摘要

Nowadays, Image enhancement finds enormous image processing applications, which are related to practical situations, Contrast enhancement is one among the different image enhancement techniques that intends to improve the image visibility. Though several works for local contrast enhancement are available in the literature, the effectiveness remains an issue and the enhancement performance needs to be improved. In this paper, a local contrast enhancement technique is proposed for both gray scale images and RGB color images. The proposed technique is comprised of two stages of enhancement, namely, local sta- tistics-based image enhancement and Genetic Algorithm based local contrast enhancement. The former stage is a pre-enhancement stage and the later is the major stage of enhancement. In the former stage, the image is processed in window basis and the local statistics of the image is obtained. Based on the local sta tistics, the image is enhanced. In the later stage, the window based operation is performed over the preenhanced image and the local contrast is enhanced. The Genetic Algorithm aids in searching of an optimalcontrast factor, which plays vital role in the contrast enhancement. The technique is evaluated with both gray scale images as well as RGB color images and performance is compared with the existing contrast enhancement techniques.
机译:如今,图像增强发现了与实际情况相关的大量图像处理应用程序,对比度增强是旨在提高图像可见度的不同图像增强技术之一。尽管文献中有几篇关于局部对比度增强的作品,但是有效性仍然是一个问题,增强性能需要改进。本文提出了一种针对灰度图像和RGB彩色图像的局部对比度增强技术。所提出的技术包括两个阶段的增强,即基于局部统计的图像增强和基于遗传算法的局部对比度增强。前一个阶段是增强前的阶段,后一个阶段是增强的主要阶段。在前阶段,以窗口为基础处理图像,并获得图像的局部统计信息。基于局部统计,图像得到了增强。在后面的阶段中,对增强后的图像执行基于窗口的操作,并增强局部对比度。遗传算法有助于寻找最佳对比度,这在增强对比度方面起着至关重要的作用。可以同时使用灰度图像和RGB彩色图像对技术进行评估,并将性能与现有的对比度增强技术进行比较。

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