论文标题
梯度域加权引导图像过滤
Gradient Domain Weighted Guided Image Filtering
论文作者
论文摘要
引导图像过滤器是图像处理中众所周知的本地过滤器。但是，光环伪像的存在是与此类过滤器相关的常见问题。本文提出了一种利用梯度信息准确识别图像边缘的算法。此外，该算法使用加权信息将平坦区域与边缘区域区分开，从而导致平坦区域的边缘更清晰和减少模糊。这种方法减轻了过度模糊的边缘，通常会导致光环伪像。实验结果表明，所提出的算法可显着抑制边缘的光环伪像，使其对图像降解和细节增强非常有效。
Guided image filter is a well-known local filter in image processing. However, the presence of halo artifacts is a common issue associated with this type of filter. This paper proposes an algorithm that utilizes gradient information to accurately identify the edges of an image. Furthermore, the algorithm uses weighted information to distinguish flat areas from edge areas, resulting in sharper edges and reduced blur in flat areas. This approach mitigates the excessive blurring near edges that often leads to halo artifacts. Experimental results demonstrate that the proposed algorithm significantly suppresses halo artifacts at the edges, making it highly effective for both image denoising and detail enhancement.
