Edge-preserving filtering based on saliency map
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摘要: 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.Abstract: 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.
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Key words:
- edge-preserving filtering /
- image smoothing /
- saliency map /
- bilateral filtering /
- guided filtering
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[1] Gonzalez R C, Woods R E.Digital image processing[M].2nd ed.New York:Prentice Hall,2002:97-98. [2] Rudin L I, Osher S,Fatemi E. Nonlinear total variation based noise removal algorithms[J].Physics D:Nonlinear Phenomena,1992,60(1):259-268. [3] Xu L, Lu C,Xu Y,et al.Image smoothing via L0 gradient minimization[J].ACM Transactions on Graphics(TOG),2011,30(6): 252-265. [4] Farbman Z, Fattal R,Lischinski D,et al.Edge-preserving decompositions for multi-scale tone and detail manipulation[J].ACM Transactions on Graphics(TOG),2008,27(3):67:1-67:10. [5] Paris S, Hasinoff S W,Kautz J.Local Laplacian filters:edge-aware image processing with a Laplacian pyramid[J].ACM Transactions on Graphics(TOG),2011,30(4):68:1-68:12. [6] Perona P, Malik J.Scale-space and edge detection using anisotropic diffusion[J].Pattern Analysis and Machine Intelligence,1990,12(7):629-639. [7] Tomasi C, Manduchi R.Bilateral filtering for gray and color images[C]//Proceedings of the IEEE International Conference on Computer Vision.Piscataway,NJ:IEEE,1998:839-846. [8] Porikli F. Constant Time O(1) bilateral filtering[C]//26th IEEE Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE,2008:1-8. [9] Yang Q, Tan K H,Ahuja N.Real-time O(1) bilateral filtering[C]//2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.Piscataway,NJ:IEEE,2009:557-564. [10] Adams A, Gelfand N,Dolson J,et al.Gaussian KD-trees for fast high-dimensional filtering[J].ACM Transactions on Graphics(TOG),2009,28(3):21:1-21:12. [11] He K, Sun J,Tang X O.Guided image filtering[C]//Computer Vision-ECCV.Heidelberg:Springer Verlag,2010:1-14. [12] Christopoulos C, Skodras A,Ebrahimi T.The JPEG2000 still image coding system:an overview[J].Consumer Electronics,2000,46(4):1103-1127. [13] Han J, Ngan K N,Li M,et al.Unsupervised extraction of visual attention objects in color images[J].Circuits and Systems for Video Technology,2006,16(1):141-145. [14] Rutishauser U, Walther D,Koch C,et al.Is bottom-up attention useful for object recognition [C]//Computer Vision and Pattern Recognition,2004.Washington,D.C.:IEEE,2004,2:II-37-II-44. [15] 李志成,秦世引, Itti Lauren.遥感图像的显著-概要特征提取与目标检测[J].北京航空航天大学学报,2010(6):659-662. Li Z C,Qin S Y,Itti L.Extraction of saliency-gist features and target detection for remote sensing images[J].Journal of Beijing University of Aeronautics and Astronautics,2010(6):659-662(in Chinese). [16] Achanta R, Hemami S,Estrada F,et al.Frequency-tuned salient region detection[C]//2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.Piscataway,NJ:IEEE,2009:1597-1604.
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