计算机科学 ›› 2018, Vol. 45 ›› Issue (11): 283-287.doi: 10.11896/j.issn.1002-137X.2018.11.045
钟菲, 杨斌
ZHONG Fei, YANG Bin
摘要: 雨滴严重影响了图像的视觉效果和后续的图像处理应用。目前,基于深度学习的单幅图像去雨方法能够有效挖掘图像的深度特征,其去雨效果优于传统方法;然而,随着网络深度的增加,网络容易出现过拟合的现象,使得去雨效果遇到瓶颈。文中在继承深度学习优点的基础上,学习有雨/无雨图像之间的残差,然后将残差与源图像进行重构,从而获得无雨图像。该方式大幅增加了网络深度,并加快了算法的收敛速度。分别利用通过不同方式获取的雨滴图像对所提方法进行实验验证,并将该方法与当前最新的去雨滴方法作比较,结果表明所提算法的去雨效果更好。
中图分类号:
[1]JOACHIMS T.Making Large-scale SVM Learning Practical [J].Advanced in Kernel Methods-Support Vector Learning,1999,8(3):499-526. [2]ZAKZESKI J,BRUIJNINCX P C,JONGERIUS A L,et al.The Catalytic Valorization of Lignin for The Production of Renewa-ble Chemicals[J].Chemical Reviews,2010,110(6):3552. [3]HUANG D A,KANG L W,WANG Y C F,et al.Self-Learning Based Image Decomposition with Applications to Single Image Denoising[J].IEEE Transactions on Multimedia,2013,16(1):83-93. [4]KANG L W,LIN C W,FU Y H.Automatic Single-image-based Rain Streaks Removal via Image Decomposition[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2011,21(4):1742-1755. [5]LUO Y,XU Y,JI H.Removing Rain from a Single Image via Discriminative Sparse Coding[C]∥Proceedings of IEEE Confe-rence on Computer Vision.Santiago:IEEE Press,2015:3397-3405. [6]YIN B C,WANG W T,WANG L C.Review of Deep Learning[J].Journal of Beijing University of Technology,2015,41(1):48-59.(in Chinese) 尹宝才,王文通,王立春.深度学习研究综述[J].北京工业大学学报,2015,41(1):48-59. [7]HE K,ZHANG X,REN S,et al.Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2015,37(9):1904-1916. [8]EIGEN D,KRISHNAN D,FERGUS R.Restoring an Image Taken through a Window Covered with Dirt or Rain[C]∥Proceedings of IEEE International Conference on Computer Vision.Sydney:IEEE Press,2013:633-640. [9]FU X,HUANG J,DING X,et al.Clearing the Skies:A Deep Network Architecture for Single-image Rain Streaks Removal[J].IEEE Transactions on Image Processing,2017,26(6):2944-2956. [10]FU X,HUANG J,ZENG D,et al.Removing Rain from Single Images via a Deep Detail Network[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Hawaii:IEEE Press,2017:1715-1723. [11]ZHANG K,CHEN Y,CHEN Y,et al.Beyond a Gaussian Denoiser:Residual Learning of Deep CNN for Image Denoising[J].IEEE Transactions on Image Processing,2016,26(7):3142-3155. [12]KIM J,LEE J K,LEE K M.Accurate Image Super-Resolution Using Very Deep Convolutional Networks [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Sichuan:IEEE Press,2016:1646-1654. [13]HINTON G E,OSINDERO S,AND TEH Y W.A Fast Lear- ning Algorithm for Deep Belief Nets[J].Neural Computation,2014,18(7):1527-1554. [14]HE K,ZHANG X,REN S,et al.Deep Residual Learning for Image Recognition[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Nevada:IEEE Press,2016:770-778. [15]DONG C,CHEN C L,HE K,et al.Image Super-Resolution Using Deep Convolutional Networks[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2016,38(2):295-307. [16]LI Y,TAN R T,GUO X,et al.Rain Streak Removal using Layer Priors[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Chengdu:IEEE Press,2016:2736-2744. [17]JIA Y Q,SHELHAMER,et al.Caffe:Convolutional Architecture for Fast Feature Embedding[C]∥Proceedings of the 22nd ACM International Conference on Multimedia.Florida:IEEE Press,2014:675-678. [18]VEDALDI A,LENC K.MatConvNet:Convolutional Neural Networks for MATLAB[C]∥Proceedings of the 23nd ACM International Conference on Multimedia.Brisbane:IEEE Press,2015:689-692. [19]SCHAEFER G.UCID:An Uncompressed Color Image Database[C]∥Proceedings of Storage & Retrieval Methods & Applications for Multimedia.CA:IEEE Press,2003:472-480. [20]BARNUM P C,NARASIMHAN S,KANADE T.Analysis of Rain and Snow in Frequency Space[J].International Journal of Computer Vision,2010,86(2):256-274. |
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