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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态图像中去除雨水

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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:去除静止图像中的雨水是一项复杂而艰巨的任务。雨滴仅影响图像的很小区域,因此导致在确定应考虑哪个区域和不应该确定哪个区域方面造成混乱。在本文中,已实施了一种新技术,该技术有效地使用了L0梯度最小化方法来去除雨点像素。最小化技术可以全局控制在图像中产生多少个非零梯度。该方法与局部特征无关,而是全局定位重要边缘。这些显着的边缘被保留,并且低幅度和无关紧要的细节被减少了。以这种方式去除雨像素。最终,使用直方图调整技术增强了去除雨水的图像的强度,以获得更好的对比度图像。实验结果表明,该算法在保持图像细节的同时,即使在大雨条件下也能有效去除雨水,是一种高效的算法。

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