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Image Contrast Enhancement Algorithm Based on GM(1,1) and Power Exponential Dynamic Decision

机译:基于GM(1,1)和幂指数动态决策的图像对比度增强算法

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摘要

Image enhancement processing is a very important operation during image preprocessing. Compared with to enhance the overall contrast level of image, enhancing the local contrast of image can improve the level of such contrast directly as well as the quality and effect of image enhancement. In this paper, the gray prediction model is applied to the process of enhancing image local contrast, so as to measure the change range of image local contrast and adaptively adjust the scale of enhancing image local contrast. The simulation results show that, in addition to enhancing the contrast of gray level on the edge of image, the proposed algorithm can inhibit roughened nonedge region and improve the quality of local enhancement processing, which create a more favorable condition for the further image edge detection.
机译:图像增强处理是图像预处理期间非常重要的操作。与增强图像的整体对比度水平相比,增强图像的局部对比度可以直接提高这种对比度的水平以及图像增强的质量和效果。本文将灰色预测模型应用于增强图像局部对比度的过程中,以测量图像局部对比度的变化范围,并自适应地调整增强图像局部对比度的范围。仿真结果表明,该算法除了增强图像边缘的灰度对比度外,还可以抑制粗糙化的非边缘区域,提高局部增强处理的质量,为进一步的图像边缘检测创造了更有利的条件。 。

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