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darkchannel
- 用MATLAB实现的darkchannel算法，实现图像去雾-Image Haze Removal Using Dark Channel
darkchannel
- 用matlab实现了暗通道图像增强，完整源代码，出自暗通道增强算法的提出者。-Dark-channel image enhancement, complete source code from the authors of the dark channel enhancement algorithms.
darkchannel
- 改进的暗原色先验算法 适用于实时处理系统 比原始程序要快很多但是质量有所降低-Improved algorithm for the dark color priori real-time processing system is much faster than the original program but the quality has decreased
darkchannel
- 本代码实现了用暗通道去雾算法实现图像的去雾处理。-This code realization with dark passage to the fog algorithm of image processing to the fog
HazeRemoval-DarkChannel-
- 图像通过暗通道可以得到图像的近似深度信息，这些信息可以实现图像的复原-The image can be obtained through the dark channel approximation of the image depth information, which can achieve the recovery of the image
darkchannel
- 此程序是“Single Image Haze Removal Using Dark Channel Prior”的程序，效果较为理想-This program is" the Single Image Haze Removal Using Dark Channel Prior" program, the effect is more ideal
darkchannel
- 黑通道去雾算法：主要是寻找图像的黑通道来估计光照，再通过图像融合技术，实现图像去雾-Black channel to fog algorithm: The main is to find an image of the black channel to estimate the light, and then through the image fusion technology, image to fog
decreasefog
- 暗通道去雾算法，环境VS2010，OPenCV2.3.1. 也可以将源码复制到自己的开发环境下直接使用，内附“说明文档”-DarkChannel defog algorithm.
darkchannel
- 暗通道去雾算法，可将风景图片实现去污效果。不会影响其原有的分辨率。效果比传统的均衡化好。-Dark channel dehazing algorithm, can achieve the decontamination effect picture. Will not affect its original resolution. Results than traditional good equalization.
darkchannel_slides
- 何凯明提出的基于darkchannel的图像去雾，效果很好，而且思想简单，PPT做的也很好，解释详细，且有参考价值-He Kaiming proposed based darkchannel image to fog, the effect is very good, and simple idea, PPT is also doing well, explained in detail, and there is a referenc
darkchannel去雾
- 此程序是何恺明博士的基于暗通道先验的图像去雾的程序。(This program is Dr. He Kaiming's program based on dark channel prior to fog)
darkchannel
- 复杂天气下对所获图像进行清晰化，采用暗通道法处理雾霾天气下的图像，获得清晰图像(Under the complicated weather clarity of the image using dark channel image processing of fog and haze, get a clear image)