Abstract
In this paper, a novel and efficient framework by exploiting Quaternionic Distance Based Weber Local Descriptor (QDWLD) and object cues is proposed for image saliency detection. In contrast to the existing saliency detection models, the advantage of the proposed approach is that it can combine quaternion number system and object cues simultaneously, which is independent of image contents and scenes. Firstly, QDWLD, which was initially designed for detecting outliers in color images, is used to represent the directional cues in an image. Meanwhile, two low-level priors, namely the Convex-Hull-Based center and color contrast cue of the image, are utilized and fused as an object-level cue. Finally, by combining QDWLD with object cues, a reliable saliency map of the image can be computed and estimated. Experimental results, based on two widely used and openly available database, show that the proposed method is able to produce reliable and promising salient maps/estimations, compared to other state-of-the-art saliency-detection models.
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References
Achanta R, Hemami S, Estrada F, et al (2009) Frequency-tuned salient region detection. IEEE Computer vision and pattern recognition, pp 1597–1604
Achanta R, Shaji A, Smith K et al (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274–2282
Cai C, Mitra SK (2000) A normalized color difference edge detector based on quaternion representation. IEEE Int Conf Image Proces (ICIP) 2:816–819
Cheng MM, Zhang Z, Lin WY, et al (2014) BING: binarized normed gradients for objectness estimation at 300 fps. IEEE conference on computer vision and pattern recognition, pp 3286–3293
Cheng MM, Mitra NJ, Huang X et al (2015) Global contrast based salient region detection. IEEE Trans Pattern Anal Mach Intell 37(3):569–582
Geng X, Hu X, Xiao J (2012) Quaternion switching filter for impulse noise reduction in color image. Signal Process 92(1):150–162
Goferman S, Zelnik-Manor L, Tal A (2012) Context-aware saliency detection. IEEE Trans Pattern Anal Mach Intell 34(10):1915–1926
Guo C, Ma Q, Zhang L (2008) Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform. IEEE conference on computer vision and pattern recognition (CVPR), pp 1–8
Guo L, Dai M, Zhu M (2014) Quaternion moment and its invariants for color object classification. Inf Sci 273:132–143
Harel J, Koch C, Perona P (2006) Graph-based visual saliency. Advances in neural information processing systems, pp 545–552
He S, Lau RWH, Yang Q (2015) Exemplar-driven top-down saliency detection via deep association. IJCV 115(3):330–344
Hou X, Zhang L (2007) Saliency detection: a spectral residual approach. IEEE Conference on Computer Vision and Pattern Recognition, pp1–8
Itti L, Koch C, Niebur E (1998) A model of saliency based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254–1259
Jian M, Lam KM, Dong J et al (2015) Visual-patch-attention-aware saliency detection. IEEE Trans. Cybern 45(8):1575–1586
Jian M, Qi Q, Sun Y, et al (2016) Saliency detection using quaternionic distance based weber descriptor and object cues. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC'2016), Korean
Jin L, Li D (2007) An efficient color-impulse detector and its application to color images. IEEE Signal Process Lett 14(6):397–400
Jin L, Liu H, Xu X et al (2013) Quaternion-based impulse noise removal from color video sequences. IEEE Trans Circuits Syst Video Technol 23(5):741–755
Lan R, Zhou Y, Tang Y (2015) Quaternionic weber local descriptor of color images. IEEE Trans Circuits Syst Video Technol. doi:10.1109/TCSVT.2492839
Lei H, Xie H, Zou W et al (2017) Hierarchical saliency detection via probabilistic object boundaries. Int J Pattern Recognit Artif Intell 31(06):1755010
Li J, Chen H, Li G et al (2015) Salient object detection based on meanshift filtering and fusion of colour information. IET Image Process 9(11):977–985
Li H, Chen J, Lu H et al (2017) CNN for saliency detection with low-level feature integration. Neurocomputing 226:212–220
Liu T, Sun J, Zheng N et al (2011) Learning to detect a salient object. IEEE Trans Pattern Anal Mach Intell 33(2):353–367
Liu Z, Xue Y, Yan H et al (2011) Efficient saliency detection based on gaussian models. IET Image Process 5(2):122–131
Ma YF, Zhang, HJ (2003) Contrast-based image attention analysis by using fuzzy growing. Proceedings of the Eleventh ACM International Conference on Multimedia, pp 374–381
Manipoonchelvi P, Muneeswaran K (2014) Region-based saliency detection. IET Image Process 8(9):519–527
MSRA, http://research.microsoft.com/en-us/um/people/jiansun/SalientObject/salient_object.htm
Oliva A, Torralba A, Castelhano MS et al (2003) Top-down control of visual attention in object detection. IEEE ICIP 1
Rahman I, Hollitt C, Zhang M (2016) Contextual-based top-down saliency feature weighting for target detection. Mach Vis Appl 27(6):893–914
Song H, Liu Z, Xie Y et al (2016) RGBD co-saliency detection via bagging-based clustering. IEEE Signal Process Lett 23(12):1707–1711
Wang A, Wang M (2017) RGB-D salient object detection via minimum barrier distance transform and saliency fusion. IEEE Signal Process Lett
Wu W, Zhao J, Zhang C, et al (2017) Improving performance of tensor-based context-aware recommenders using bias tensor factorization with context feature auto-encoding. Knowledge-Based Systems
Xie Y, Lu H (2011) Visual saliency detection based on Bayesian model. IEEE International Conference on Image Processing, pp 645-648
Xie Y, Lu H, Yang MH (2013) Bayesian saliency via low and mid-level cues. IEEE Trans Image Process 22(5):1689–1698
Yan Q, Xu L, Shi J, Jia J (2013) Hierarchical saliency detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Yan C, Zhang Y, Xu J, Dai F, Li L, Dai Q, Wu F (2014) A highly parallel framework for HEVC coding unit partitioning tree decision on many-core processors. IEEE Signal Process Lett 21(5):573–576
Yan C, Zhang Y, Dai F, Wang X, Li L, Dai Q (2014) Parallel deblocking filter for HEVC on many-core processor. Electron Lett 50(5):367–368
Yan C, Zhang Y, Dai F, Zhang J, Li L, Dai Q (2014) Efficient parallel HEVC intra-prediction on many-core processor. Electron Lett 50(11):805–806
Yan C, Zhang Y, Xu J, Dai F, Zhang J, Dai Q, Wu F (2014) Efficient parallel framework for HEVC motion estimation on many-core processors. IEEE Trans Circuits Syst Video Technol 24(12):2077–2089
Yang J, Yang MH (2017) Top-down visual saliency via joint crf and dictionary learning. IEEE Trans Pattern Anal Mach Intell 39(3):576–588
Yang C, Zhang L, Lu H (2013) Graph-regularized saliency detection with convex-hull-based center prior. IEEE Signal Process Lett 20(7):637–640
Zhai Y, Shah M (2006) Visual attention detection in video sequences using spatiotemporal cues. ACM international conference on multimedia, pp 815–824
Zhang J, Sclaroff S (2016) Exploiting Surroundedness for saliency detection: a Boolean map approach. IEEE Trans Pattern Anal Mach Intell 38(5):889–902
Zhong G, Liu R, Cao J et al (2016) A generalized nonlocal mean framework with object-level cues for saliency detection. Vis Comput 32(5):611–623
Zhong SH, Liu Y, Ng TY, Liu Y (2016) Perception-oriented video saliency detection via spatio-temporal attention analysis. Neurocomputing 207:178–188
Zhou J, Gao S, Yan Y et al (2014) Saliency detection framework via linear neighbourhood propagation. IET Image Process 8(12):804–814
Zhou W, Song T, Li L et al (2014) Multi-scale contrast-based saliency enhancement for salient object detection. IET Comput Vis 8(3):207–215
Acknowledgements
We would like to thank Dr. Rushi Lan in the Faculty of Science and Technology, University of Macau for providing the QDWLD Matlab code.
This work was supported by National Natural Science Foundation of China (NSFC) (61601427, 61602229); Natural Science Foundation of Shandong Province (ZR2015FQ011); China Postdoctoral Science Foundation funded project (2016 M590659); Postdoctoral Science Foundation of Shandong Province (201603045); Qingdao Postdoctoral Science Foundation funded project (861605040008) and Applied Basic Research Project of Qingdao (16-5-1-4-jch); The Fundamental Research Funds for the Central Universities (201511008, 30020084851); & Technology Cooperation Program of China (ISTCP) (2014DFA10410).
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Jian, M., Qi, Q., Dong, J. et al. Saliency detection using quaternionic distance based weber local descriptor and level priors. Multimed Tools Appl 77, 14343–14360 (2018). https://doi.org/10.1007/s11042-017-5032-z
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DOI: https://doi.org/10.1007/s11042-017-5032-z