Visual descriptors for content-based retrieval of remote-sensing images

International Journal of Remote Sensing

Volumn 39, Issue 5, 2018, Pages 1343-1376

  Napoletano, Paolo ^a  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CONTENT BASED RETRIEVAL; LAND USE; NEURAL NETWORKS; REMOTE SENSING; URANIUM COMPOUNDS;

COARSE-GRAINED; CONTENT BASED IMAGE RETRIEVAL; CONVOLUTIONAL NEURAL NETWORK; HIGH RESOLUTION SATELLITES; LAND USE/LAND COVER; REMOTE SENSING IMAGES; UNIVERSITY OF CALIFORNIA; VECTOR OF LOCALLY AGGREGATED DESCRIPTORS;

IMAGE TEXTURE;

ARTIFICIAL NEURAL NETWORK; IMAGE ANALYSIS; IMAGE PROCESSING; REMOTE SENSING;

EID: 85040811567     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2017.1399472     Document Type: Article

References (77)

1. Aptoula, E. 2014. “Remote Sensing Image Retrieval with Global Morphological Texture Descriptors.” Geoscience and Remote Sensing, IEEE Transactions On 52 (5): 3023–3034. doi:10.1109/TGRS.2013.2268736.
2. Arandjelovic, R., P. Gronat, A. Torii, T. Pajdla, and J. Sivic. 2016. “NetVLAD: CNN Architecture for Weakly Supervised Place Recognition.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 5297–5307.
3. Arvis, V., C. Debain, M. Berducat, and A. Benassi. 2004. “Generalization of the Cooccurrence Matrix for Colour Images: Application to Colour Texture.” Image Analysis & Stereology 23: 1.
4. Baeza-Yates, Ricardo, Berthier Ribeiro-Neto, et al. 1999. Modern Information Retrieval. Vol. 463. New York: ACM press.
5. Barilla, M. E., and M. Spann. 2008. “Colour-Based Texture Image Classification Using the Complex Wavelet Transform.” In Electrical Engineering, Computing Science and Automatic Control, 2008. CCE 2008. 5th International Conference On, 358–363.
6. Bianco, S., D. Mazzini, D. P. Pau, and R. Schettini. 2015. “Local Detectors and Compact Descriptors for Visual Search: A Quantitative Comparison.” Digital Signal Processing 44: 1–13. doi:10.1016/j.dsp.2015.06.001.
7. Bianconi, F., and A. Fernández. 2007. “Evaluation of the Effects of Gabor Filter Parameters on Texture Classification.” Pattern Recognition 40 (12): 3325–3335. doi:10.1016/j.patcog.2007.04.023.
8. Bianconi, F., R. Harvey, P. Southam, and A. Fernández. 2011. “Theoretical and Experimental Comparison of Different Approaches for Color Texture Classification.” Journal of Electronic Imaging 20: 4. doi:10.1117/1.3651210.
9. Bosilj, P., E. Aptoula, S. Lefèvre, and E. Kijak. 2016. “Retrieval of Remote Sensing Images with Pattern Spectra Descriptors.” ISPRS International Journal of Geo-Information 5 (12): 228. doi:10.3390/ijgi5120228.
10. Brinke, W., D. M. Squire, and J. Bigelow. 2004. “Similarity: Measurement, Ordering and Betweenness.” In Knowledge-Based Intelligent Information and Engineering Systems, 996–1002. Berlin/Heidelberg: Springer.
11. Chatfield, K., K. Simonyan, A. Vedaldi, and A. Zisserman. 2014. “Return of the Devil in the Details: Delving Deep into Convolutional Nets.” In arXiv Preprint arXiv:1405.3531.
12. Chatzichristofis, S. A., and Y. S. Boutalis. 2008. “CEDD: Color and Edge Directivity Descriptor: A Compact Descriptor for Image Indexing and Retrieval.” In Computer Vision Systems, 312–322. Berlin/Heidelberg: Springer.
13. Cimpoi, M., S. Maji, I. Kokkinos, S. Mohamed, and A. Vedaldi. 2014. “Describing Textures in the Wild.” In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference On, 3606–3613.
14. Ciocca, G., I. Gagliardi, and R. Schettini. 2001. “Quicklook 2: An Integrated Multimedia System.” Journal of Visual Languages & Computing 12 (1): 81–103. doi:10.1006/jvlc.2000.0188.
15. Ciocca, G., and R. Schettini. 1999. “A Relevance Feedback Mechanism for Content-Based Image Retrieval.” Information Processing & Management 35 (5): 605–632. doi:10.1016/S0306-4573(99)00021-7.
16. Csurka, G., C. Dance, L. Fan, J. Willamowski, and C. Bray. 2004. “Visual Categorization with Bags of Keypoints.” Workshop on Statistical Learning in Computer Vision, ECCV. Vol. 1, 1–2.
17. Prague Cusano, C., P. Napoletano, and R. Schettini. 2015. “Remote Sensing Image Classification Exploiting Multiple Kernel Learning.” IEEE Geoscience and Remote Sensing Letters 12 (11): 2331–2335. doi:10.1109/LGRS.2015.2476365.
18. Dai, D., and W. Yang. 2011. “Satellite Image Classification via Two-Layer Sparse Coding with Biased Image Representation.” Geoscience and Remote Sensing Letters 8 (1): 173–176. doi:10.1109/LGRS.2010.2055033.
19. Datta, R., D. Joshi, L. Jia, and J. Z. Wang. 2008. “Image Retrieval: Ideas, Influences, and Trends of the New Age.” ACM Computing Surveys (CSUR) 40 (2): 5. doi:10.1145/1348246.1348248.
20. Delhumeau, J., P.-H. Gosselin, H. Jégou, and P. Patrick. 2013. “Revisiting the VLAD Image Representation.” In Proceedings of the 21st ACM International Conference on Multimedia, 653–656.New York, NY: ACM.
21. Demir, B., and L. Bruzzone. 2015. “A Novel Active Learning Method in Relevance Feedback for Content-Based Remote Sensing Image Retrieval.” Geoscience and Remote Sensing, IEEE Transactions On 53 (5): 2323–2334. doi:10.1109/TGRS.2014.2358804.
22. Deng, J., W. Dong, R. Socher, L. Li-Jia, L. Kai, and L. Fei-Fei. 2009. “Imagenet: A Large-Scale Hierarchical Image Database.” In IEEE Conference on Computer Vision and Pattern Recognition, 248–255.IEEE.
23. Deselaers, T., D. Keysers, and H. Ney. 2008. “Features for Image Retrieval: An Experimental Comparison.” Information Retrieval 11 (2): 77–107. doi:10.1007/s10791-007-9039-3.
24. Douze, M., H. Jégou, and F. Perronnin. 2016. “Polysemous Codes.” In European Conference on Computer Vision, 785–801. Berlin/Heidelberg: Springer.
25. Ferecatu, M., and N. Boujemaa. 2007. “Interactive Remote-Sensing Image Retrieval Using Active Relevance Feedback.” Geoscience and Remote Sensing, IEEE Transactions On 45 (4): 818–826. doi:10.1109/TGRS.2007.892007.
26. Grauman, K., and B. Leibe. 2010. Visual Object Recognition. Morgan & Claypool Publishers.
27. Hanbury, A., U. Kandaswamy, and D. Adjeroh. 2005. “Illumination-Invariant Morphological Texture Classification.” In: Mathematical Morphology: 40 Years On, edited by C. Ronse, L. Najman, and E. Decencire, Vol. 30, of Computational Imaging and Vision, 377–386. Netherlands: Springer Berlin/ Heidelberg.
28. Haralick, R. M. 1979. “Statistical and Structural Approaches to Texture.” Proceedings of the IEEE 67 (5): 786–804. doi:10.1109/PROC.1979.11328.
29. Hauta-Kasari, M., J. Parkkinen, T. Jaaskelainen, and R. Lenz. 1996. “Generalized Co-Occurrence Matrix for Multispectral Texture Analysis.” In Pattern Recognition, 1996., Proceedings of the 13th International Conference On, Vol. 2, aug, 785–789.
30. He, K., X. Zhang, S. Ren, and J. Sun. 2016. “Deep Residual Learning for Image Recognition.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 770–778.
31. Hong, P., Q. Tian, and T. S. Huang. 2000. “Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevance Feedback.” In International Conference on Image Processing. Vol. 3, 750–753. IEEE.
32. Jain, A., and G. Healey. 1998. “A Multiscale Representation Including Opponent Color Features for Texture Recognition.” Image Processing, IEEE Transactions On 7 (1): 124–128. doi:10.1109/83.650858.
33. Jégou, H., M. Douze, C. Schmid, and P. Patrick 2010. “Aggregating Local Descriptors into a Compact Image Representation.” In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 3304–3311.
34. Jia, Y., E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. 2014. “Caffe: Convolutional Architecture for Fast Feature Embedding.” In arXiv Preprint arXiv:1408.5093.
35. Junior, O. L., D. Delgado, V. Gonçalves, and U. Nunes. 2009. “Trainable Classifier-Fusion Schemes: An Application to Pedestrian Detection.” Intelligent Transportation Systems, ITSC'09. 12th International IEEE Conference on IEEE USA.
36. Krizhevsky, A., I. Sutskever, and G. E. Hinton. 2012. “Imagenet Classification with Deep Convolutional Neural Networks.” In Advances in Neural Information Processing Systems, 1097–1105. NewYork, NY: Curran Associates Inc.
37. Li, J., and N. M. Allinson. 2013. “Relevance Feedback in Content-Based Image Retrieval: A Survey.” In Handbook on Neural Information Processing, 433–469. Berlin/Heidelberg: Springer.
38. Liu, G.-H., and J.-Y. Yang. 2013. “Content-Based Image Retrieval Using Color Difference Histogram.” Pattern Recognition 46 (1): 188–198. doi:10.1016/j.patcog.2012.06.001.
39. Lowe, D. G. 2004. “Distinctive Image Features from Scale-Invariant Keypoints.” International Journal of Computer Vision 60 (2): 91–110. doi:10.1023/B:VISI.0000029664.99615.94.
40. Lu, J., V. E. Liong, and J. Zhou. 2017. “Deep Hashing for Scalable Image Search.” IEEE Transactions on Image Processing 26 (5): 2352–2367. doi:10.1109/TIP.2017.2678163.
41. Mäenpää, T., and M. Pietikäinen. 2004. “Classification with Color and Texture: Jointly or Separately?.” Pattern Recognition 37 (8): 1629–1640. doi:10.1016/j.patcog.2003.11.011.
42. Manjunath, B. S., J.-R. Ohm, V. V. Vasudevan, and A. Yamada. 2001. “Color and Texture Descriptors.” Circuits and Systems for Video Technology, IEEE Transactions On 11 (6): 703–715. doi:10.1109/76.927424.
43. Manjunath, B. S., and M. Wei-Ying. 1996. “Texture Features for Browsing and Retrieval of Image Data.” Pattern Analysis and Machine Intelligence, IEEE Transactions On 18 (8): 837–842. doi:10.1109/34.531803.
44. Manning, C. D., P. Raghavan, and H. Schütze. 2008. Introduction to Information Retrieval. Vol. 1. Cambridge: Cambridge university press.
45. Marmanis, D., M. Datcu, T. Esch, and U. Stilla. 2016. “Deep Learning Earth Observation Classification Using ImageNet Pretrained Networks.” IEEE Geoscience and Remote Sensing Letters 13 (1): 105–109. doi:10.1109/LGRS.2015.2499239.
46. Mirmehdi, M., X. Xie, and J. Suri. 2009. Handbook of Texture Analysis. London, UK: Imperial College Press.
47. Novak, Carol L, Steven Shafer, et al. 1992. “Anatomy of a Color Histogram.” In Computer Vision and Pattern Recognition, 1992. Proceedings CVPR’92., 1992 IEEE Computer Society Conference On, 599–605. IEEE.
48. Ojala, T., M. Pietikäinen, and T. Mänepää. 2002. “Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns.” IEEE Transactions Pattern Analysis Mach Intelligent 24 (7): 971–987. doi:10.1109/TPAMI.2002.1017623.
49. Oliva, A., and A. Torralba. 2001. “Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope.” International Journal of Computer Vision 42 (3): 145–175. doi:10.1023/A:1011139631724.
50. Ozkan, S., T. Ates, E. Tola, M. Soysal, and E. Esen. 2014. “Performance Analysis of State-Of-the-Art Representation Methods for Geographical Image Retrieval and Categorization.” Geoscience and Remote Sensing Letters, IEEE 11 (11): 1996–2000. doi:10.1109/LGRS.2014.2316143.
51. Pedronette, D. C. Guimarães, R. T. Calumby, and R. D. S. Torres. 2015. “A Semi-Supervised Learning Algorithm for Relevance Feedback and Collaborative Image Retrieval.” EURASIP Journal on Image and Video Processing 2015 (1): 1–15.
52. Pietikainen, M., S. Nieminen, E. Marszalec, and T. Ojala. 1996. “Accurate Color Discrimination with Classification Based on Feature Distributions.” In Pattern Recognition, 1996., Proceedings of the 13th International Conference On, Vol. 3, aug, 833–838.
53. Razavian, A. S., H. Azizpour, J. Sullivan, and S. Carlsson. 2014. “CNN Features Off-The-Shelf: An Astounding Baseline for Recognition.” In Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on, 512–519.
54. Rui, Y., and T. S. Huang. 2001. “Relevance Feedback Techniques in Image Retrieval.” In Principles of Visual Information Retrieval, 219–258. Berlin/Heidelberg: Springer.
55. Rui, Y., T. S. Huang, and S.-F. Chang. 1999. “Image Retrieval: Current Techniques, Promising Directions, and Open Issues.” Journal of Visual Communication and Image Representation 10 (1): 39–62. doi:10.1006/jvci.1999.0413.
56. Rui, Y., T. S. Huang, M. Ortega, and S. Mehrotra. 1998. “Relevance Feedback: A Power Tool for Interactive Content-Based Image Retrieval.” Circuits and Systems for Video Technology, IEEE Transactions On 8 (5): 644–655. doi:10.1109/76.718510.
57. Russakovsky, O., J. Deng, S. Hao, J. Krause, S. Satheesh, M. Sean, Z. Huang, et al. 2015. “ImageNet Large Scale Visual Recognition Challenge.” International Journal of Computer Vision (IJCV) 115 (3): 211–252. DOI:10.1007/s11263-015-0816-y.
58. Schmidhuber, J. 2015. “Deep Learning in Neural Networks: An Overview.” Neural Networks 61: 85–117. doi:10.1016/j.neunet.2014.09.003.
59. Sermanet, P., D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and L. Yann. 2014. “OverFeat: Integrated Recognition, Localization and Detection Using Convolutional Networks.” International Conference on Learning Representations (ICLR 2014). April. CBLS.
60. Simonyan, K., and A. Zisserman. 2014. “Very Deep Convolutional Networks for Large-Scale Image Recognition.” In arXiv Preprint arXiv:1409.1556.
61. Sivic, J., and A. Zisserman. 2003. “Video Google: A Text Retrieval Approach to Object Matching in Videos.” In Computer Vision, 2003. Proceedings. Ninth IEEE International Conference On, 1470–1477. IEEE.
62. Smeulders, A. W. M., M. Worring, S. Santini, A. Gupta, and R. Jain. 2000. “Content-Based Image Retrieval at the End of the Early Years.” Pattern Analysis and Machine Intelligence, IEEE Transactions On 22 (12): 1349–1380. doi:10.1109/34.895972.
63. Szegedy, C., W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. 2015. “Going Deeper with Convolutions.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1–9.
64. Thomee, B., and M. S. Lew. 2012. “Interactive Search in Image Retrieval: A Survey.” International Journal of Multimedia Information Retrieval 1 (2): 71–86. doi:10.1007/s13735-012-0014-4.
65. Torii, A., J. Sivic, T. Pajdla, and M. Okutomi. 2013. “Visual Place Recognition with Repetitive Structures.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 883–890.
66. Tsai, C.-F. 2012. “Bag-Of-Words Representation in Image Annotation: A Review.” In ISRN Artificial Intelligence, 2012.
67. Vedaldi, A., and K. Lenc. 2014. “MatConvNet – Convolutional Neural Networks for MATLAB.” CoRR. abs/1412.4564.
68. Veltkamp, R., H. Burkhardt, and H.-P. Kriegel. 2013. State-Of-The-Art in Content-Based Image and Video Retrieval. Vol. 22. Berlin/Heidelberg: Springer Science & Business Media.
69. Wang, X.-Y., W. Jun-Feng, and H.-Y. Yang. 2010. “Robust Image Retrieval Based on Color Histogram of Local Feature Regions.” Multimedia Tools and Applications 49 (2): 323–345. doi:10.1007/s11042-009-0362-0.
70. Xia, G.-S., H. Jingwen, H. Fan, B. Shi, X. Bai, Y. Zhong, L. Zhang, and L. Xiaoqiang. 2017. “AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification.” IEEE Transactions on Geoscience and Remote Sensing 55: 3965–3981. doi:10.1109/TGRS.2017.2685945.
71. Xia, Gui-Song, Wen Yang, Julie Delon, Yann Gousseau, Hong Sun, Henri Matre, et al. 2010. “Structural High-Resolution Satellite Image Indexing.” ISPRS TC VII Symposium-100 Years ISPRS 38:298–303.
72. Yang, Y., and S. Newsam. 2010. “Bag-Of-Visual-Words and Spatial Extensions for Land-Use Classification.” In Proc. Of the Int’l Conf. On Advances in Geographic Information Systems, 270–279. New York, NY: ACM.
73. Yang, Y., and S. Newsam. 2013. “Geographic Image Retrieval Using Local Invariant Features.” Geoscience and Remote Sensing, IEEE Transactions On 51 (2): 818–832. doi:10.1109/TGRS.2012.2205158.
74. Zaji, G., N. Koji, V. Radosavljevi, M. Rudinac, S. Rudinac, N. Reljin, I. Reljin, and B. Reljin. 2007. “Accelerating of Image Retrieval in CBIR System with Relevance Feedback.” EURASIP Journal on Advances in Signal Processing 2007 (1): 1–13. doi:10.1155/2007/62678.
75. Zeiler, M. D., and R. Fergus. 2014. “Visualizing and Understanding Convolutional Networks.” In Computer Vision–ECCV 2014, 818–833. Berlin/Heidelberg: Springer.
76. Zhao, F., Y. Huang, L. Wang, and T. Tan. 2015. “Deep Semantic Ranking Based Hashing for Multi- Label Image Retrieval.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1556–1564.
77. Zhou, X. S., and T. S. Huang. 2003. “Relevance Feedback in Image Retrieval: A Comprehensive Review.” Multimedia Systems 8 (6): 536–544. doi:10.1007/s00530-002-0070-3.