基于显著特性的保持边缘滤波算法

针对传统保持边缘滤波算法中存在光晕的缺点,提出了基于显著特性的图像保持边缘滤波算法.该算法主要思想是利用原图的显著特性图具有边缘突出的特点,简化双边滤波法中灰度因子的设定工作.首先提取出原图像的显著图,然后根据图像显著值的大小自适应模糊图像中的细节和噪声部分:显著值较小的区域灰度因子设置较大,平滑此区域;显著值较大的区域灰度因子设置较小,保持边缘部分的清晰.实验结果表明,该算法在平滑了细节和噪声的同时,有效地保持了边缘信息的清晰,与传统方法相比,新方法不仅避免了光晕现象的产生,而且应用更为广泛. 

Edge-preserving filtering based on saliency map

A new edge-preserving filtering algorithm based on the saliency map was proposed to avoid the halo effect along salient edges in traditional edge-preserving filtering. The saliency map was characterized by the salient edges in the image and insensibility to noise. The key idea of our filtering algorithm was to simplify the decision of gray standard deviation in bilateral filtering by using the characteristics. We first obtained a saliency map of the original image, and then blurred the image adaptively according to the local saliency value. If the local saliency value is high, the standard deviation would become small to retain the region. If the local saliency value is low, the standard deviation would become large to smooth the region. Therefore, the filtering proposed could avoid unwanted smoothing near salient edges. Experiments show that the proposed filtering performs better in comparison with guided filtering and bilateral filtering. A variety of applications including high dynamic range (HDR) Tone mapping and stylization by our filtering algorithm are also demonstrated.