Steering Kernel-Based Guided Image Filter for Single Image Dehazing

S. Yadav, K. Sarawadekar
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引用次数: 5

Abstract

The guided image filter (GIF) technique is used for haze removal. It reduces the gradient reversal artifact as well as preserves the edge information precisely in smooth (flat) region only. However, it fails to avoid halo artifact and edge-smoothing effect in sharp regions. So, to mitigate this problem, we propose an adaptive haze removal algorithm using a steering kernel-based guided image filter (SKGIF). Steering kernel determines the edge-direction in guidance image more adequately. The edge-direction is an essential feature of guidance image, and it helps to determine more edge-preserving information in flat as well as sharp regions. Experimental outcomes on different hazy images prove the effectiveness of the proposed algorithm.
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基于引导核的单幅图像去雾滤波
引导图像滤波(GIF)技术用于雾霾去除。它减少了梯度反转伪影,并且仅在光滑(平坦)区域精确地保留了边缘信息。但它不能避免光晕伪影和锐利区域的边缘平滑效应。因此,为了缓解这个问题,我们提出了一种使用基于导向核的引导图像滤波器(SKGIF)的自适应雾霾去除算法。转向核更充分地决定了制导图像的边缘方向。边缘方向是制导图像的一个重要特征,它有助于在平面和尖锐区域确定更多的边缘保持信息。在不同模糊图像上的实验结果证明了该算法的有效性。
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