| 图像的局部自适应Gamma校正 |
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| 引用本文： | 储清翠,王华彬,陶亮.图像的局部自适应Gamma校正[J].计算机工程与应用,2015,51(7):189-193. |
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| 作者姓名： | 储清翠 王华彬 陶亮 |
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| 作者单位： | 安徽大学 计算机科学与技术学院，合肥 230601 |
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| 基金项目： | 国家自然科学基金(No.61071169)。 |
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| 摘 要： | 照度不均匀图像的分辨率较低，高光区与阴影区会隐藏很多的图像信息。针对照度不均匀导致成像的不同区域存在不同的光照效果，提出了一种新的局部自适应Gamma校正方法，先使用K近邻法估计出图像中不同区域的合适的Gamma值，再对图像进行局部的Gamma校正。实验证明了该方法具有较好的校正效果。
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| 关 键 词： | 照度不均匀 局部自适应 Gamma校正 K近邻（KNN） |
Local adaptive Gamma correction method |
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| CHU Qingcui,WANG Huabin,TAO Liang.Local adaptive Gamma correction method[J].Computer Engineering and Applications,2015,51(7):189-193. |
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| Authors: | CHU Qingcui WANG Huabin TAO Liang |
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| Affiliation: | School of Computer, Anhui University, Hefei 230601, China |
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| Abstract: | Uneven illumination images have low resolution and the high light regions and the shadow regions of the images often hide a lot of image information. This paper presents a new local adaptive Gamma correction method to solve the problem that different regions have different light effects due to uneven illumination. This method uses the KNN（K-Nearest Neighbor） algorithm to estimate the most appropriate Gamma value in different regions of an image for local Gamma correction in each of the different regions. Experimental results demonstrate that the proposed method performs better in estimating Gamma values and improving image quality. |
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| Keywords: | uneven illumination local self-adaptability Gamma correction KNN(K-Nearest Neighbor) |
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