局部平均显著梯度保边滤波算法

摘要

针对传统平均保边滤波算法中存在的光晕伪影现象,提出一种显著图局部平均梯度的保边滤波算法.利用显著图像边缘对比度突出的特点,简化边缘区域和非边缘区域间的阈值设定工作,并根据显著图的平均梯度自适应的平滑图像中的细节和噪声部分,同时保持边缘清晰.实验结果表明,显著图局部平均梯度的保边滤波算法利用显著特性有效地避免了传统平均滤波算法中的光晕伪影现象. 相对于传统平均滤波算法,在降噪、多尺度增强以及HDR方面都有较好的表现.%To avoid the halo artifact in the traditional filters, a new edge-preserving filter based on local average saliency gradient was proposed. The criterion to determine whether or not a region should be smoothed is difficult to give, hence it will introduce the "halo" artifact along the edges by unwanted smoothing in an image. Our idea is motivate by the feature of saliency map that enhances the salient edges in an image. Using the feature, we simplify the work to determine whether or not a region should be smoothed, and smooth the image adaptively according to local average saliency gradient. We retain the region with high average saliency gradient, and smooth the region with low average saliency gradient. Experiments show that our method performs better than traditional edge-preserving filters in smoothing, multi-enhancement, and HDR while avoiding "halo".