基于改进非局部均值滤波算法的显著性区域检测
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摘要
针对传统非局部均值(NL-Means)滤波算法缺乏对人类视觉系统考虑的问题,提出一种基于改进非局部均值滤波算法框架的显著性区域检测算法.首先利用作为低层线索的颜色独特性生成初级显著图,然后利用对象性测度估计算法提取出对象候选集,再将对象性测度估计分数扩展到每个超像素区域,生成高层线索的前景先验和背景先验显著图,最后将3个显著图进行多尺度融合并作为改进滤波算法的对象级线索,经滤波得到最终显著图.在基准数据集MSRA-1000和ECSSD上,与目前流行的检测算法进行了主观定性和客观定量比较,实验结果表明,该算法不仅在均匀高亮显著对象的同时抑制背景区域,而且在准确率、召回率和F-measure等评价指标上也有较大提升.
Aiming at the problem that the traditional Nonlocal Mean( NL-Means) filtering algorithm lacks the consideration of human vision system,this paper proposes a saliency region detection algorithm based on the improved Nonlocal Mean filtering algorithm.Firstly,the primary graph is generated by using the color uniqueness as the low-level clue.Then,the objectness estimation is utilized to generalize a set of object proposals,and the object measure estimation score is pooled to each superpixel patch to generate the foreground and background saliency map as the high-level clues.Finally,the improved Nonlocal Mean filtering framework with the object-level cue which multi-scale fuses the low-level saliency map with high-level saliency map generates the final saliency maps.A series of experiments are done on MSRA-1000,ECSSD dataset and results show that,compared with the current popular detection algorithms,the proposed algorithm not only suppresses the background areas while uniformly highlighting the salient objects,but also improves the performance evaluation of precision,recall and F-measure values.
Aiming at the problem that the traditional Nonlocal Mean( NL-Means) filtering algorithm lacks the consideration of human vision system,this paper proposes a saliency region detection algorithm based on the improved Nonlocal Mean filtering algorithm.Firstly,the primary graph is generated by using the color uniqueness as the low-level clue.Then,the objectness estimation is utilized to generalize a set of object proposals,and the object measure estimation score is pooled to each superpixel patch to generate the foreground and background saliency map as the high-level clues.Finally,the improved Nonlocal Mean filtering framework with the object-level cue which multi-scale fuses the low-level saliency map with high-level saliency map generates the final saliency maps.A series of experiments are done on MSRA-1000,ECSSD dataset and results show that,compared with the current popular detection algorithms,the proposed algorithm not only suppresses the background areas while uniformly highlighting the salient objects,but also improves the performance evaluation of precision,recall and F-measure values.
引文
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[32]Treisman A M,Gelade G.A feature integration theory of attention[J].Cogn Psych,1980,12(1):97-136.
[33]LI J,TIAN Y,HUANG T,et al,Multi-task rank learning for visual saliency estimation[J].IEEE Transactions on Circuits and Systems for Video Technology,2011,99(5):623-636.
[34]魏蕊,何明一,廉保旺,等.目标尺寸先验与图像抽象的显著性检测[J].西安电子科技大学学报:自然科学版,2017,44(1):182-188.WEI R,HE M Y,LIAN B W.et al.Saliency detection via object size distribution prior and image abstraction[J].Journal of Xidian University:Natural Science,2017,44(1):182-188.
[35]MURRAY N,VANRELL M,OTAZU X,et al.Saliency estimation using a non-parametric low-level vision model[C].IEEE Conference on Computer Vision and Pattern Recognition,2011:433-440.
[36]ZHAI Y,SHAH M.Visual attention detection in video sequences using spatiotemporal cues[C].Proceedings of the 14th Annual ACM International Conference on Multimedia,2006:815-824.
[37]ACHANTA R,ESTRADA F,WILS P,et al.Salient region detection and segmentation[C].Lecture Notes in Computer Science,2008:66-75.
[38]ACHANTA R,SUSSTRUNK S.Saliency detection using maximum symmetric surround[C].Proceedings of IEEEInternational Conference on Image Processing,2010:2 653-2 656.
[2]HOU X D,ZHANG L Q.Saliency detection:a spectral residual approach[C].Proceedings of IEEE Conference on Computer Vision and Pattern Recognitions,2007:1-8.
[3]ITTI L,KOCH C,NIEBUR E.A model of saliency-based visual attention for rapid scene analysis[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1998,20(11):1 254-1 259.
[4]PAN J,SU Z,BIAN M,et al.Saliency detection based on an edge-preserving filter[C].IEEE International Conference on Image Processing,2013:1 757-1 761.
[5]WEI Y C,WEN F,ZHU W J,et al.Geodesic saliency using background priors[C].European Conference on Computer Vision,2012:29-42.
[6]SHI Y,YI Y,YAN H,et al.Region contrast and supervised locality-preserving projection-based saliency detection[J].The Visual Computer,2015,31(9):1 191-1 205.
[7]MARGOLIN R,ZELNIK-MANOR L,TAL A.Saliency for image manipulation[J].The Visual Computer,2013,29(5):381-392.
[8]LIU T,YUAN Z J,SUN J,et al.Learning to detect a salient object[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,32(2):353-367.
[9]SHEN X,WU Y.A unified approach to salient object detection via low rank matrix recovery[C].Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2012,23(10):853-860.
[10]YANG J,YANG M.Top-down visual saliency via joint CRF and dictionary learning[C].Proceedings of IEEEConference on Computer Vision and Pattern Recognition,2012,157(10):2 296-2 303.
[11]GOFERMAN S,ZELNIK-MANOR L,TAL A.Contextaware saliency detection[J].IEEE Transactions on Pattern Analysis&Machine Interlligence,2012,34(10):1 915-1 926.
[12]JIANG H Z,WANG J D,YUAN Z J,et al.Automatic salient object segmentation based on context and shape prior[C].Proceedings of the British Machine Vision Conference,2011:1-12.
[13]ACHANTA R,HEMAMI S,ESTRADA F.Frequencytuned salient region detection[C].Proceedings of IEEEConference on Computer Vision and Pattern Recognition,2009:1 597-1 604.
[14]PERAZZI F,KRAHENBUHL P,PRITCH Y,et al.Saliency filters:contrast based filtering for salient region detection[C].Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2012:773-740.
[15]HAREL J,KOCH C,PERONA P.Graph-based visual saliency[J].Advances in Neural Information Processing System,2006,19:545-552.
[16]YAN Q,XU L,SHI J P,et al.Hierarchical saliency detection[C].Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2013:1 155-1 162.
[17]JUDD T,EHINGER K,DURAND F.Learning to predict where humans look[C].Proceedings of the 12th International Conference on Computer Vision,2009:2 106-2 113.
[18]林晓,王燕玲,朱恒亮,等.改进凸包的贝叶斯模型显著性检测算法[J].计算机辅助设计与图形学学报.2017,29(2):222-228.LIN X,WANG Y L,ZHU H L,et al.Saliency detection based on the bayesian model of improved convex Hull[J].Journal of Computer-Aided Design&Computer Graphics,2017,29(2):222-228.
[19]JIA Y,HAN M.Category-independent object-level saliency detection[C].IEEE International Conference on Computer Vision,2013:1 761-1 768.
[20]JIANG H Z,WANG J D,YUAN Z J.Salient object detection:a discriminative regional feature integration approachh[C].Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2013:2 083-2 090.
[21]BUADES A,COLL B,MOREL J.A non-local algorithm for image denoising[J].IEEE Computer Society Conference on Computer Vision,2005,2(7):60-65.
[22]BEEK P V,YANG J,YAMAMOTO S,et al.Image deblurring and denoising with non-local regularization constraint[C].Proceedings of the International Society for Optical Engineering,2010,7543(2):868-869.
[23]PERONA P,MALIK J.Scale-space and edge detection using anisotropic diffusion[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1990,12(7):629-639.
[24]CHENG M M,ZHANG Z,LIN W Y,et al.BING:Binarized normed gradients for objectness estimation at300fps[C].Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2014:3 286-3 293.
[25]YAROSLAVSKY LEONID P,YAROSLAVSKIJ L P.Digital picture processing:An introduction[J].Springer Verlag,1986,1(2):113-116.
[26]TOMASI C,MANDUCHI R.Bilateral filtering for gray and color images[C].IEEE International Conference on Computer Vision,1998:839-846.
[27]RADHAKRISHNA A,APPU S,KEVIN S,et al.Slic superpixels compared to state-of-the-art superpixel methods[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(11):2 274-2 282.
[28]MA Y F,ZHANG H J.Contrast-based Image Attention Analysis by Using Fuzzy Growing[C].Proceedings of the ACM International Multimedia Conference and Exhibition,2003:374-381.
[29]BORJI A,SIHITE D,ITTI L.Salient object detection:Abenchmark[C].Proceedings of the 12th European conference on Computer Vision,2012,24(12):414-429.
[30]WOLFE J M,HOROWITZ T S.What attributes guide the deployment of visual attention and how do they do it?[J].Nature Reviews Neuroscience,2004,5(6):495-501.
[31]DESIMONE R,DUNCAN J.Neural mechanisms of selective visual attention[J].Annual Review of Neuroscience,1995,18(1):193-222.
[32]Treisman A M,Gelade G.A feature integration theory of attention[J].Cogn Psych,1980,12(1):97-136.
[33]LI J,TIAN Y,HUANG T,et al,Multi-task rank learning for visual saliency estimation[J].IEEE Transactions on Circuits and Systems for Video Technology,2011,99(5):623-636.
[34]魏蕊,何明一,廉保旺,等.目标尺寸先验与图像抽象的显著性检测[J].西安电子科技大学学报:自然科学版,2017,44(1):182-188.WEI R,HE M Y,LIAN B W.et al.Saliency detection via object size distribution prior and image abstraction[J].Journal of Xidian University:Natural Science,2017,44(1):182-188.
[35]MURRAY N,VANRELL M,OTAZU X,et al.Saliency estimation using a non-parametric low-level vision model[C].IEEE Conference on Computer Vision and Pattern Recognition,2011:433-440.
[36]ZHAI Y,SHAH M.Visual attention detection in video sequences using spatiotemporal cues[C].Proceedings of the 14th Annual ACM International Conference on Multimedia,2006:815-824.
[37]ACHANTA R,ESTRADA F,WILS P,et al.Salient region detection and segmentation[C].Lecture Notes in Computer Science,2008:66-75.
[38]ACHANTA R,SUSSTRUNK S.Saliency detection using maximum symmetric surround[C].Proceedings of IEEEInternational Conference on Image Processing,2010:2 653-2 656.