1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016
Abstract This paper systematically introduces the research achievements of modeling and removal algorithms for rain, snow and fog in recent years from authors' team. It includes a depth estimation and scattering removal algorithm based on near-filed illumination, a fog removal algorithm based on far parallel illumination and region optimization, and a snowflake removal algorithm based on low-rank decomposition as well as a raindrop & snowflake removal algorithm based on matrix decomposition.
Fund:Supported by National Natural Science Foundation of China(No.91648118,61473280)
About author:: TIAN Jiandong, Ph.D., professor. His research interests include robot vision.LIU Lianqing, Ph.D., professor. His research interests include robot perception.
[1] NARASIMHAN S G, GUPTA M, DONNER C, et al. Acquiring Scattering Properties of Participating Media by Dilution. ACM Transactions on Graphics, 2006, 25(3): 1003-1012. [2] SUN B, RAMAMOORTHI R, NARASIMHAN S G, et al. A Practical Analytic Single Scattering Model for Real Time Rendering. ACM Transactions on Graphics, 2008, 24(3): 1040-1049. [3] NARASIMHAN S G, NAYAR S K. Contrast Restoration of Weather Degraded Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(6): 713-724. [4] TAN R T. Visibility in Bad Weather From a Single Image // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Washington, USA: IEEE, 2008. DOI: 10.1109/CVPR.2008.4587643. [5] TAREL J P, HAUTIÈRE N. Fast Visibility Restoration from a Single Color or Gray Level Image // Proc of the 12th IEEE International Conference on Computer Vision. Washington, USA: IEEE, 2009: 2201-2208. [6] HE K M, SUN J, TANG X O. Single Image Haze Removal Using Dark Channel Prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353. [7] HE K M, SUN J, TANG X O. Guided Image Filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409. [8] ANCUTI C O, ANCUTI C, HERMANS C, et al. A Fast Semi-inverse Approach to Detect and Remove the Haze From a Single Image // Proc of the Asian Conference on Computer Vision. Berlin, Germany: Springer, 2010: 501-514. [9] MENG G F, WANG Y, DUAN J Y, et al. Efficient Image Dehazing with Boundary Constraint and Contextual Regularization // Proc of the IEEE International Conference on Computer Vision. Washington, USA: IEEE, 2013: 617-624. [10] TANG K T, YANG J C, WANG J. Investigating Haze-Relevant Features in a Learning Framework for Image Dehazing // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Washington, USA: IEEE, 2014: 2995-3002. [11] TIAN J D, MUREZ Z, CUI T, et al. Depth and Image Restoration from Light Field in a Scattering Medium // Proc of the IEEE International Conference on Computer Vision. Washington, USA: IEEE, 2017: 2420-2429. [12] CUI T, TIAN J D, WANG E D, et al. Single Image Dehazing by Latent Region-Segmentation Based Transonission Estimation and Weighted L1-norm Regularisation. IET Image Processing, 2017, 11(2): 145-154. [13] GARG K, NAYAR S K. Detection and Removal of Rain from Videos // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Washington, USA: IEEE, 2004: 528-535. [14] CHEN Z, SHEN J H. A New Algorithm of Rain(Snow) Removal in Video. Journal of Multimedia, 2013, 8(2): 168-174. [15] BARNUM P C, NARASIMHAN S, KANADE T. Analysis of Rain and Snow in Frequency Space. International Journal of Computer Vision, 2010, 86(2/3): 256-274. [16] KANG L W, LIN C W, FU Y H. Automatic Single-Image-Based Rain Streaks Removal via Image Decomposition. IEEE Transactions on Image Processing, 2012, 21(4): 1742-1755. [17] CHEN D Y, CHEN C C, KANG L W. Visual Depth Guided Color Image Rain Streaks Removal Using Sparse Coding. IEEE Transac-tions on Circuits and Systems for Video Technology, 2014, 24(8): 1430-1455. [18] YAO C, WANG C, HONG L J, et al. A Bayesian Probabilistic Framework for Rain Detection. Entropy, 2014, 16(6): 3302-3314. [19] SAKAINO H. A Semitransparency-Based Optical-Flow Method with a Point Trajectory Model for Particle-Like Video. IEEE Transactions on Image Processing, 2012, 21(2): 441-450. [20] CHEN J, CHAU L P. A Rain Pixel Recovery Algorithm for Videos with Highly Dynamic Scenes. IEEE Transactions on Image Processing, 2014, 23(3): 1097-1104. [21] BOSSU J, HAUTIÈRE N, TAREL J P. Rain or Snow Detection in Image Sequences through Use of a Histogram of Orientation of Streaks. International Journal of Computer Vision, 2011, 93(3): 348-367. [22] TIAN J D, HAN Z, REN W H, et al. Snowflake Removal for Videos via Global and Local Low-rank Decomposition. IEEE Transactions on Multimedia, 2018, 20(10): 2659-2669. [23] REN W H, TIAN J D, HAN Z, et al. Video Desnowing and Deraining Based on Matrix Decomposition // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Washington, USA: IEEE, 2017: 2838-2847. [24] CANDÉS E J, LI X D, MA Y, et al. Robust Principal Component Analysis? Journal of the ACM, 2011, 58(3). DOI: 10.1145/1970392.1970395. [25] ZHOU X W, YAN J, YU W C. Moving Object Detection by Detecting Contiguous Outliers in the Low-Rank Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(3): 597-610. [26] ORCHARD M T, SULLIVAN G J. Overlapped Block Motion Compensation: An Estimation-theoretic Approach. IEEE Transactions on Image Processing, 1994, 3(5): 693-699. [27] ELAD M, AHARON M. Image Denoising via Sparse and Redundant Representations over Learned Dictionaries. IEEE Transactions on Image Processing, 2006, 15(12): 3736-3745. [28] DONG W S, SHI G M, LI X. Nonlocal Image Restoration with Bilateral Variance Estimation: A Low-Rank Approach. IEEE Transactions on Image Processing, 2013, 22(2): 700-711. [29] JI H, LIU C Q, SHEN Z W, et al. Robust Video Denoising Using Low Rank Matrix Completion // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Washington, USA: IEEE, 2009: 1791-1798. [30] DABOV K, FOI A, KATKOVNIK V, et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering. IEEE Transactions on Image Processing, 2007, 16(8): 2080-2095. [31] MAIRAL J, BACH F, PONCE J, et al. Non-local Sparse Models for Image Restoration // Proc of the 12th IEEE International Conference on Computer Vision. Washington, USA: IEEE, 2009: 2272-2279. [32] ZORAN D, WEISS Y. From Learning Models of Natural Image Patches to Whole Image Restoration // Proc of the International Conference on Computer Vision. Washington, USA: IEEE, 2011: 479-486.
2019, Vol. 32 
