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Rain removal from still images using L0 gradient minimization technique

机译:使用L0梯度最小化技术从静止图像中雨移除

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Removal of rain from still images is a complex and a challenging task. The rain drops affects only on a very small region of an image, and hence, leading to a confusion to determine which region should be considered and which should not. In this paper, a new technique has been implemented which effectively uses the L0 gradient minimization approach to remove the rain pixels. The minimization technique can globally control how many non-zero gradients are resulted in the image. The method is independent of local features, but instead locates important edges globally. These salient edges are preserved and low amplitude and insignificant details are diminished. The rain pixels are removed in this manner. Finally the rain removed images are enhanced in intensity using histogram adjustment technique to get better contrast images. Experimental results show that the proposed algorithm is highly efficient as it removes rain effectively even under heavy rain conditions, while preserving the details of the image.
机译:从静止图像中删除雨是一个复杂的并且有挑战性的任务。雨滴仅在图像的一个非常小的区域上影响,因此,导致困惑地确定应该考虑哪个区域并且不应该。在本文中,已经实施了一种新技术,其有效地使用L0梯度最小化方法去除雨像素。最小化技术可以全局控制图像中有多少非零梯度。该方法与本地特征无关,而是在全球范围内定位重要边缘。这些凸缘被保存,并且低幅度和微不足道的细节减少。以这种方式除去雨像素。最后,使用直方图调整技术,在强度上增强了雨被移除的图像,以获得更好的对比图像。实验结果表明,该算法高效,因为即使在大雨条件下有效地除去雨,同时保留图像的细节。

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