Abstract
Saliency can be modeled as spatially localized and contrasted structures with higher blob density and higher blob evenness across scales in images. And it is likely to contain regions and objects of interest. So saliency detection is desired before further image processing and analysis. This paper presented an automatic and effective method for saliency detection in satellite images, based on multi-scale blob information. Firstly, multi-scale blob information were extracted from input images, to produce a blob map. Then, in the blob map, multi-level distance transform spread the blob information to the entire image, to generate a saliency map. Finally the saliency map was segmented to detect salient regions and to locate object centers. The experimental results illustrated its accuracy and stability for detecting salient regions (such as residential areas, parking lots and airplane docks) and for locating object centers in various satellite images.
Similar content being viewed by others
References
Chalmond, B., Francesconi, B., & Herbin, S. (2006). Using hidden scale for salient object detection[J]. Image Processing, IEEE Transactions on, 15(9), 2644–2656.
Chen, H. Z., Jing, N., Wang, J., Chen, Y. G., & Chen, L. (2014). A novel saliency detection method for lunar remote sensing images[J]. Geoscience and Remote Sensing Letters, IEEE, 11(1), 24–28.
Cui, X., Tian, Y., & Ma, L. (2014). Top-Down Visual Saliency Detection in Optical Satellite Images Based on Local Adaptive Regression Kernel[J]. Journal of Multimedia, 9(1), 173–180.
Harel J, Koch C, Perona P. Graph-based visual saliency[C]//Advances in neural information processing systems. 2006: 545–552.
Hu, X., Shen, J., Shan, J., & Pan, L. (2013). Local edge distributions for detection of salient structure textures and objects[J]. Geoscience and Remote Sensing Letters, IEEE, 10(3), 466–470.
Itti, L., Koch, C., & Niebur, E. (1998). A Model of Saliency-Based Visual Attention for Rapid Scene Analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11), 1254–1259.
Jäger, M., & Hellwich, O. (2005). Saliency and salient region detection in SAR polarimetry[C]. International Geoscience And Remote Sensing Symposium, 4, 2791.
Klein, D. A., & Frintrop, S. (2011). Center-surround divergence of feature statistics for salient object detection[C] Computer Vision (ICCV), 2011 I.E. International Conference on. IEEE, 2011: 2214–2219.
Li, Z., & Itti, L. (2011). Saliency and gist features for target detection in satellite images[J]. Image Processing, IEEE Transactions on, 20(7), 2017–2029.
Li, W., & Pan, C. (2011). Saliency-based automatic target detection in remote sensing images[M] Advanced Research on Computer Science and Information Engineering. Springer Berlin Heidelberg, 2011: 327-333.
Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 60(2), 91–110.
Otsu, N. (1975). A threshold selection method from gray-level histograms[J]. Automatica, 11(285), 23–27.
Rosin, P. L. (2009). A simple method for detecting salient regions[J]. Pattern Recognition, 42(11), 2363–2371.
Shapiro, L. G., & Stockman, G. C. (2001). Computer vision. Prentence Hall, 137–150.
Wang, X., Lv, Q., Wang, B., & Zhang, L. (2013). Airport detection in remote sensing images: a method based on saliency map[J]. Cognitive Neurodynamics, 7(2), 143–154.
Xu G, Huo H, Fang T, & Li D. (2007). Extracting salient object from remote sensing image based on guidance of visual attention[C] International Symposium on Multispectral Image Processing and Pattern Recognition. International Society for Optics and Photonics, 2007: 67902 W.
Yang, Q., Tan, K. H., & Ahuja, N. (2009). Real-time O(1) bilateral filtering[C] Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. IEEE, 557–564.
Zhang, L., Qiu, B., Yu, X., & Xu, J. (2015). Multi-scale hybrid saliency analysis for region of interest detection in very high resolution remote sensing images[J]. Image and Vision Computing, 35, 1–13.
Acknowledgments
This work was supported in part by China Postdoctoral Science Foundation under Grant 2015M570138, in part by the National Natural Science Foundation of China under Grant 41301488 and 41301438, in part by the National High Technology Research and Development Program of China (863 Program) under Grant 2013AA12A401-2, in part by the National Major Program on High Resolution Earth Observation System under Grant 03-Y30B06-9001-13/15-01.
Conflict of interest
The authors report no conflict of interest. The authors are responsible for the content and writing of the paper.
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Zhou, Y., Luo, J., Hu, X. et al. Multi-Scale Blobs for Saliency Detection in Satellite Images. J Indian Soc Remote Sens 44, 159–166 (2016). https://doi.org/10.1007/s12524-015-0469-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12524-015-0469-x