{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:25:47Z","timestamp":1761060347210,"version":"3.37.3"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2017,5,10]],"date-time":"2017-05-10T00:00:00Z","timestamp":1494374400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2017,9]]},"DOI":"10.1007\/s11263-017-1015-9","type":"journal-article","created":{"date-parts":[[2017,5,10]],"date-time":"2017-05-10T08:00:29Z","timestamp":1494403229000},"page":"204-222","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Joint Image Denoising and Disparity Estimation via Stereo Structure PCA and Noise-Tolerant Cost"],"prefix":"10.1007","volume":"124","author":[{"given":"Jianbo","family":"Jiao","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4378-2335","authenticated-orcid":false,"given":"Qingxiong","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Shengfeng","family":"He","sequence":"additional","affiliation":[]},{"given":"Shuhang","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Rynson W. H.","family":"Lau","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,10]]},"reference":[{"key":"1015_CR1","doi-asserted-by":"crossref","unstructured":"Alter, F., Matsushita, Y., & Tang, X. (2006). An intensity similarity measure in low-light conditions. In ECCV.","DOI":"10.1007\/11744085_21"},{"issue":"4","key":"1015_CR2","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1109\/34.677269","volume":"20","author":"S Birchfield","year":"1998","unstructured":"Birchfield, S., & Tomasi, C. (1998). A pixel dissimilarity measure that is insensitive to image sampling. IEEE TPAMI, 20(4), 401\u2013406.","journal-title":"IEEE TPAMI"},{"key":"1015_CR3","doi-asserted-by":"crossref","unstructured":"Buades, A., Coll, B., & Morel, J. (2005). A non-local algorithm for image denoising. In CVPR (pp. 60\u201365).","DOI":"10.1109\/CVPR.2005.38"},{"issue":"2","key":"1015_CR4","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1137\/040616024","volume":"4","author":"A Buades","year":"2005","unstructured":"Buades, A., Coll, B., & Morel, J. M. (2005). A review of image denoising algorithms, with a new one. Multiscale Modeling and Simulation, 4(2), 490\u2013530.","journal-title":"Multiscale Modeling and Simulation"},{"issue":"2","key":"1015_CR5","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s11263-007-0052-1","volume":"76","author":"A Buades","year":"2008","unstructured":"Buades, A., Coll, B., & Morel, J. M. (2008). Nonlocal image and movie denoising. IJCV, 76(2), 123\u2013139.","journal-title":"IJCV"},{"key":"1015_CR6","doi-asserted-by":"crossref","unstructured":"Burger, H., Schuler, C., & Harmeling, S. (2012). Image denoising: Can plain neural networks compete with BM3D? In CVPR (pp. 2392\u20132399).","DOI":"10.1109\/CVPR.2012.6247952"},{"issue":"8","key":"1015_CR7","first-page":"3711","volume":"23","author":"S Chan","year":"2014","unstructured":"Chan, S., Zickler, T., & Lu, Y. (2014). Monte Carlo non-local means: Random sampling for large-scale image filtering. IEEE TIP, 23(8), 3711\u20133725.","journal-title":"IEEE TIP"},{"key":"1015_CR8","doi-asserted-by":"crossref","unstructured":"Chen, F., Zhang, L., & Yu, H. (2015). External patch prior guided internal clustering for image denoising. In ICCV(pp. 603\u2013611).","DOI":"10.1109\/ICCV.2015.76"},{"issue":"8","key":"1015_CR9","first-page":"2080","volume":"16","author":"K Dabov","year":"2007","unstructured":"Dabov, K., Foi, A., Katkovnik, V., & Egiazarian, K. (2007). Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE TIP, 16(8), 2080\u20132095.","journal-title":"IEEE TIP"},{"issue":"13","key":"1015_CR10","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1016\/j.patrec.2011.06.027","volume":"32","author":"L De-Maeztu","year":"2011","unstructured":"De-Maeztu, L., Villanueva, A., & Cabeza, R. (2011). Stereo matching using gradient similarity and locally adaptive support-weight. Pattern Recognition Letters, 32(13), 1643\u20131651.","journal-title":"Pattern Recognition Letters"},{"key":"1015_CR11","doi-asserted-by":"crossref","unstructured":"Deledalle, C., Salmon, J., & Dalalyan, A. (2011). Image denoising with patch based PCA: Local versus global. In BMVC (pp. 425\u2013455).","DOI":"10.5244\/C.25.25"},{"key":"1015_CR12","doi-asserted-by":"crossref","unstructured":"Dong, W., Li, G., Shi, G., Li, X., & Ma, Y. (2015). Low-rank tensor approximation with Laplacian scale mixture modeling for multiframe image denoising. In ICCV (pp. 442\u2013449).","DOI":"10.1109\/ICCV.2015.58"},{"issue":"1","key":"1015_CR13","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/s11263-006-7899-4","volume":"70","author":"P Felzenszwalb","year":"2006","unstructured":"Felzenszwalb, P., & Huttenlocher, D. (2006). Efficient belief propagation for early vision. IJCV, 70(1), 41\u201354.","journal-title":"IJCV"},{"key":"1015_CR14","unstructured":"Fu, Y., Lam, A., Sato, I., & Sato, Y. (2016). Adaptive spatial-spectral dictionary learning for hyperspectral image restoration. IJCV, 122, 1\u201318."},{"issue":"3","key":"1015_CR15","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1109\/34.276126","volume":"16","author":"G Healey","year":"1994","unstructured":"Healey, G., & Kondepudy, R. (1994). Radiometric CCD camera calibration and noise estimation. IEEE TPAMI, 16(3), 267\u2013276.","journal-title":"IEEE TPAMI"},{"key":"1015_CR16","doi-asserted-by":"crossref","unstructured":"Heo, Y., Lee, K., & Lee, S. (2007). Simultaneous depth reconstruction and restoration of noisy stereo images using non-local pixel distribution. In CVPR (pp. 1\u20138).","DOI":"10.1109\/CVPR.2007.382999"},{"issue":"4","key":"1015_CR17","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1109\/TPAMI.2010.136","volume":"33","author":"Y Heo","year":"2011","unstructured":"Heo, Y., Lee, K., & Lee, S. (2011). Robust stereo matching using adaptive normalized cross-correlation. IEEE TPAMI, 33(4), 807\u2013822.","journal-title":"IEEE TPAMI"},{"issue":"2","key":"1015_CR18","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/TPAMI.2007.1166","volume":"30","author":"H Hirschm\u00fcller","year":"2008","unstructured":"Hirschm\u00fcller, H. (2008). Stereo processing by semiglobal matching and mutual information. IEEE TPAMI, 30(2), 328\u2013341.","journal-title":"IEEE TPAMI"},{"issue":"1","key":"1015_CR19","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1023\/A:1014554110407","volume":"47","author":"H Hirschm\u00fcller","year":"2002","unstructured":"Hirschm\u00fcller, H., Innocent, P., & Garibaldi, J. (2002). Real-time correlation-based stereo vision with reduced border errors. IJCV, 47(1), 229\u2013246.","journal-title":"IJCV"},{"issue":"9","key":"1015_CR20","doi-asserted-by":"crossref","first-page":"1582","DOI":"10.1109\/TPAMI.2008.221","volume":"31","author":"H Hirschm\u00fcller","year":"2009","unstructured":"Hirschm\u00fcller, H., & Scharstein, D. (2009). Evaluation of stereo matching costs on images with radiometric differences. IEEE TPAMI, 31(9), 1582\u20131599.","journal-title":"IEEE TPAMI"},{"key":"1015_CR21","doi-asserted-by":"crossref","unstructured":"Honda, H., Timofte, R., & Gool, L.V. (2015). Make my day\u2014high-fidelity color denoising with near-infrared. In CVPR workshops (pp. 82\u201390).","DOI":"10.1109\/CVPRW.2015.7301300"},{"key":"1015_CR22","unstructured":"Joshi, N., & Cohen, M. (2010). Seeing Mt. Rainier: Lucky imaging for multi-image denoising, sharpening, and haze removal. In ICCP (pp. 1\u20138)."},{"key":"1015_CR23","doi-asserted-by":"crossref","unstructured":"Jung, I., Sim, J., Kim, C., & Lee, S. (2013). Robust stereo matching under radiometric variations based on cumulative distributions of gradients. In ICIP (pp. 2082\u20132085).","DOI":"10.1109\/ICIP.2013.6738429"},{"key":"1015_CR24","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.patrec.2016.04.015","volume":"78","author":"Y Kim","year":"2016","unstructured":"Kim, Y., Koo, J., & Lee, S. (2016). Adaptive descriptor-based robust stereo matching under radiometric changes. Pattern Recognition Letters, 78, 41\u201347.","journal-title":"Pattern Recognition Letters"},{"key":"1015_CR25","doi-asserted-by":"crossref","unstructured":"Levin, A., & Nadler, B. (2011). Natural image denoising: Optimality and inherent bounds. In CVPR (pp. 2833\u20132840).","DOI":"10.1109\/CVPR.2011.5995309"},{"key":"1015_CR26","doi-asserted-by":"crossref","unstructured":"Levin, A., Nadler, B., Durand, F., & Freeman, W. (2012). Patch complexity, finite pixel correlations and optimal denoising. In ECCV (pp. 73\u201386).","DOI":"10.1007\/978-3-642-33715-4_6"},{"key":"1015_CR27","doi-asserted-by":"crossref","unstructured":"Liu, C., & Freeman, W. (2010). A high-quality video denoising algorithm based on reliable motion estimation. In ECCV (pp. 706\u2013719).","DOI":"10.1007\/978-3-642-15558-1_51"},{"issue":"12","key":"1015_CR28","first-page":"5469","volume":"24","author":"X Lu","year":"2015","unstructured":"Lu, X., Lin, Z., Jin, H., Yang, J., & Wang, J. (2015). Image-specific prior adaptation for denoising. IEEE TIP, 24(12), 5469\u20135478.","journal-title":"IEEE TIP"},{"issue":"7","key":"1015_CR29","first-page":"2167","volume":"24","author":"E Luo","year":"2015","unstructured":"Luo, E., Chan, S., & Nguyen, T. (2015). Adaptive image denoising by targeted databases. IEEE TIP, 24(7), 2167\u20132181.","journal-title":"IEEE TIP"},{"key":"1015_CR30","doi-asserted-by":"crossref","unstructured":"Luo, E., Chan, S., Pan, S., & Nguyen, T. (2013). Adaptive non-local means for multiview image denoising: Searching for the right patches via a statistical approach. In ICIP (pp. 543\u2013547).","DOI":"10.1109\/ICIP.2013.6738112"},{"issue":"1","key":"1015_CR31","first-page":"119","volume":"22","author":"M Maggioni","year":"2013","unstructured":"Maggioni, M., Katkovnik, V., Egiazarian, K., & Foi, A. (2013). Nonlocal transform-domain filter for volumetric data denoising and reconstruction. IEEE TIP, 22(1), 119\u2013133.","journal-title":"IEEE TIP"},{"issue":"1","key":"1015_CR32","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/nn986","volume":"6","author":"M Menz","year":"2003","unstructured":"Menz, M., & Freeman, R. (2003). Stereoscopic depth processing in the visual cortex: a coarse-to-fine mechanism. Nature Neuroscience, 6(1), 59\u201365.","journal-title":"Nature Neuroscience"},{"key":"1015_CR33","doi-asserted-by":"crossref","unstructured":"Menze, M., & Geiger, A. (2015). Object scene flow for autonomous vehicles. In CVPR (pp. 3061\u20133070).","DOI":"10.1109\/CVPR.2015.7298925"},{"key":"1015_CR34","doi-asserted-by":"crossref","unstructured":"Mosseri, I., Zontak, M., & Irani, M. (2013). Combining the power of internal and external denoising. In ICIP (pp. 1\u20139).","DOI":"10.1109\/ICCPhot.2013.6528298"},{"key":"1015_CR35","doi-asserted-by":"crossref","unstructured":"Muresan, D., & Parks, T. (2003). Adaptive principal components and image denoising. In ICIP (pp. 101\u2013104).","DOI":"10.1109\/ICIP.2003.1246908"},{"key":"1015_CR36","unstructured":"Nir, T., Kimmel, R., & Bruckstein, A. (2005). Variational approach for joint optic-flow computation and video restoration. Technical report CIS200503, Technion, Israel Institute of Technology."},{"key":"1015_CR37","doi-asserted-by":"crossref","unstructured":"Park, B., Lee, K., & Lee, S. (2006). A new similarity measure for random signatures: Perceptually modified Hausdorff distance. In ACIVS (pp. 990\u20131001).","DOI":"10.1007\/11864349_90"},{"key":"1015_CR38","doi-asserted-by":"crossref","unstructured":"Romeny, B. M. T. H., & Florack, L. (1993). A multiscale geometric model of human vision. In W. R. Hendee & P. N. T. Wells (Eds.), Perception of visual information, Chap. 4 (pp. 73\u2013114).","DOI":"10.1007\/978-1-4757-6769-8_4"},{"issue":"1","key":"1015_CR39","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1023\/A:1014573219977","volume":"47","author":"D Scharstein","year":"2002","unstructured":"Scharstein, D., & Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV, 47(1), 7\u201342.","journal-title":"IJCV"},{"key":"1015_CR40","unstructured":"Scharstein, D., & Szeliski, R. (2007). Middlebury stereo dataset. http:\/\/vision.middlebury.edu\/stereo\/data\/ ."},{"issue":"7","key":"1015_CR41","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1109\/TCYB.2013.2278548","volume":"44","author":"L Shao","year":"2014","unstructured":"Shao, L., Yan, R., & Li, X. (2014). From heuristic optimization to dictionary learning: A review and comprehensive comparison of image denoising algorithms. IEEE Transsction on Cybernetics, 44(7), 1001\u20131013.","journal-title":"IEEE Transsction on Cybernetics"},{"issue":"12","key":"1015_CR42","doi-asserted-by":"crossref","first-page":"2518","DOI":"10.1109\/TPAMI.2015.2417569","volume":"37","author":"X Shen","year":"2015","unstructured":"Shen, X., Yan, Q., Xu, L., Ma, L., & Jia, J. (2015). Multispectral joint image restoration via optimizing a scale map. IEEE TPAMI, 37(12), 2518\u20132530.","journal-title":"IEEE TPAMI"},{"key":"1015_CR43","doi-asserted-by":"crossref","unstructured":"Tan, X., Sun, C., Wang, D., Guo, Y., & Pham, T. (2014). Soft cost aggregation with multi-resolution fusion. In ECCV (pp. 17\u201332).","DOI":"10.1007\/978-3-319-10602-1_2"},{"key":"1015_CR44","unstructured":"Vemulapalli, R., Tuzel, O., & Liu, M. (2015). Deep Gaussian conditional random field network: A model-based deep network for discriminative denoising. arXiv:1511.04067 ."},{"issue":"8","key":"1015_CR45","first-page":"3428","volume":"23","author":"D Vu","year":"2014","unstructured":"Vu, D., Chidester, B., Yang, H., Do, M., & Lu, J. (2014). Efficient hybrid tree-based stereo matching with applications to postcapture image refocusing. IEEE TIP, 23(8), 3428\u20133442.","journal-title":"IEEE TIP"},{"key":"1015_CR46","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/s11263-016-0886-5","volume":"119","author":"J Xu","year":"2016","unstructured":"Xu, J., Yang, Q., Tang, J., & Feng, Z. (2016). Linear time illumination invariant stereo matching. IJCV, 119, 179\u2013193.","journal-title":"IJCV"},{"key":"1015_CR47","doi-asserted-by":"crossref","unstructured":"Xu, J., Zhang, L., Zuo, W., Zhang, D., & Feng, X. (2015). Patch group based nonlocal self-similarity prior learning for image denoising. In ICCV (pp. 244\u2013252).","DOI":"10.1109\/ICCV.2015.36"},{"key":"1015_CR48","doi-asserted-by":"crossref","unstructured":"Xu, L., & Jia, J. (2010). Two-phase kernel estimation for robust motion deblurring. In ECCV (pp. 157\u2013170).","DOI":"10.1007\/978-3-642-15549-9_12"},{"key":"1015_CR49","doi-asserted-by":"crossref","unstructured":"Yue, H., Sun, X., Yang, J., & Wu, F. (2014). Cid: Combined image denoising in spatial and frequency domains using web images. In CVPR (pp. 2933\u20132940).","DOI":"10.1109\/CVPR.2014.375"},{"issue":"6","key":"1015_CR50","first-page":"1967","volume":"24","author":"H Yue","year":"2015","unstructured":"Yue, H., Sun, X., Yang, J., & Wu, F. (2015). Image denoising by exploring external and internal correlations. IEEE TIP, 24(6), 1967\u20131982.","journal-title":"IEEE TIP"},{"key":"1015_CR51","doi-asserted-by":"crossref","unstructured":"Zabih, R., & Woodfill, J. (1994). Non-parametric local transforms for computing visual correspondence. In ECCV (pp. 151\u2013158).","DOI":"10.1007\/BFb0028345"},{"issue":"1","key":"1015_CR52","first-page":"2287","volume":"17","author":"J Zbontar","year":"2016","unstructured":"Zbontar, J., & LeCun, Y. (2016). Stereo matching by training a convolutional neural network to compare image patches. Journal of Machine Learning Research, 17(1), 2287\u20132318.","journal-title":"Journal of Machine Learning Research"},{"key":"1015_CR53","doi-asserted-by":"crossref","unstructured":"Zhang, K., Fang, Y., Min, D., Sun, L., Yang, S., Yan, S., et al. (2014). Cross-scale cost aggregation for stereo matching. In CVPR (pp. 1590\u20131597).","DOI":"10.1109\/CVPR.2014.206"},{"issue":"4","key":"1015_CR54","doi-asserted-by":"crossref","first-page":"1531","DOI":"10.1016\/j.patcog.2009.09.023","volume":"43","author":"L Zhang","year":"2010","unstructured":"Zhang, L., Dong, W., Zhang, D., & Shi, G. (2010). Two-stage image denoising by principal component analysis with local pixel grouping. Pattern Recognition, 43(4), 1531\u20131549.","journal-title":"Pattern Recognition"},{"key":"1015_CR55","doi-asserted-by":"crossref","unstructured":"Zhang, L., Vaddadi, S., Jin, H., & Nayar, S. (2009). Multiple view image denoising. In CVPR (pp. 1542\u20131549).","DOI":"10.1109\/CVPR.2009.5206836"},{"key":"1015_CR56","doi-asserted-by":"crossref","unstructured":"Zontak, M., Mosseri, I., & Irani, M. (2013). Separating signal from noise using patch recurrence across scales. In CVPR (pp. 1195\u20131202).","DOI":"10.1109\/CVPR.2013.158"},{"key":"1015_CR57","doi-asserted-by":"crossref","unstructured":"Zoran, D., & Weiss, Y. (2011) From learning models of natural image patches to whole image restoration. In ICCV (pp. 479\u2013486).","DOI":"10.1109\/ICCV.2011.6126278"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11263-017-1015-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-017-1015-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-017-1015-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,24]],"date-time":"2019-09-24T02:14:36Z","timestamp":1569291276000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11263-017-1015-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,10]]},"references-count":57,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,9]]}},"alternative-id":["1015"],"URL":"https:\/\/doi.org\/10.1007\/s11263-017-1015-9","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"type":"print","value":"0920-5691"},{"type":"electronic","value":"1573-1405"}],"subject":[],"published":{"date-parts":[[2017,5,10]]}}}