Removal of rain video based on temporal intensity and chromatic constraint of raindrops

An improved algorithm of frame time difference is proposed and applied to raindrops removal of video image.This paper analyzes the temporal intensity waveform and chromatic constraint properties of raindrops, and the method is optimized by these two properties. We make use of the difference between rain and non-rain moving objects in the pixels’ intensity changes, which realized a broad classification between the rain and non-rain moving object pixel. The candidate raindrops pixels are optimized in combination with the chromatic constraint property. The experimental results show that the proposed algorithm has a better effect of rainy day in video image restoration than Garg’s, and it is simple and effective. The algorithm has a strong applicability, and it can be further used for many applications, such as air pollution control, management, outdoor surveillance, remote sensing and intelligent vehicles.

[1]  Yu Luo,et al.  Removing Rain from a Single Image via Discriminative Sparse Coding , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[2]  Li-Wei Kang,et al.  Visual Depth Guided Color Image Rain Streaks Removal Using Sparse Coding , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  Byung Cheol Song,et al.  Multi-frame de-raining algorithm using a motion-compensated non-local mean filter for rainy video sequences , 2015, J. Vis. Commun. Image Represent..

[4]  Sudipta Mukhopadhyay,et al.  Removal of rain from videos: a review , 2014, Signal Image Video Process..

[5]  Xiaoou Tang,et al.  Image Super-Resolution Using Deep Convolutional Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Malekshahi Gelareh,et al.  Detection and Removal of Rain from Video Using Predominant Direction of Gabor Filters , 2015 .

[7]  Jérémie Bossu,et al.  Rain or Snow Detection in Image Sequences Through Use of a Histogram of Orientation of Streaks , 2011, International Journal of Computer Vision.

[8]  Takeo Kanade,et al.  Analysis of Rain and Snow in Frequency Space , 2008, International Journal of Computer Vision.

[9]  Katsushi Ikeuchi,et al.  Adherent Raindrop Modeling, Detectionand Removal in Video , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Kyoung Mu Lee,et al.  Accurate Image Super-Resolution Using Very Deep Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Jian Wang,et al.  Frequency Domain Directional Filtering Based Rain Streaks Removal from a Single Color Image , 2014, ICIC.

[12]  Vijayan K. Asari,et al.  Utilizing Local Phase Information to Remove Rain from Video , 2014, International Journal of Computer Vision.

[13]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[14]  Chul Lee,et al.  Single-image deraining using an adaptive nonlocal means filter , 2013, 2013 IEEE International Conference on Image Processing.

[15]  S. Nayar,et al.  Detection and removal of rain from videos , 2004, CVPR 2004.

[16]  Michael S. Brown,et al.  Rain Streak Removal Using Layer Priors , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Yuandong Tian,et al.  Seeing through water: Image restoration using model-based tracking , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[18]  Yu-Chiang Frank Wang,et al.  Exploiting image structural similarity for single image rain removal , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[19]  Yu-Hsiang Fu,et al.  Automatic Single-Image-Based Rain Streaks Removal via Image Decomposition , 2012, IEEE Transactions on Image Processing.

[20]  Li-Wei Kang,et al.  Self-Learning Based Image Decomposition With Applications to Single Image Denoising , 2014, IEEE Transactions on Multimedia.

[21]  Jing Xu,et al.  Removal of rain in video based on motion and shape characteristics of raindrops , 2014 .

[22]  Charless C. Fowlkes,et al.  Contour Detection and Hierarchical Image Segmentation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Chia-Hung Yeh,et al.  Self-learning-based single image super-resolution of a highly compressed image , 2013, 2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP).

[24]  Chiou-Ting Hsu,et al.  A Generalized Low-Rank Appearance Model for Spatio-temporally Correlated Rain Streaks , 2013, 2013 IEEE International Conference on Computer Vision.

[25]  Chang-Su Kim,et al.  Video Deraining and Desnowing Using Temporal Correlation and Low-Rank Matrix Completion , 2015, IEEE Transactions on Image Processing.

[26]  Sudipta Mukhopadhyay,et al.  A Probabilistic Approach for Detection and Removal of Rain from Videos , 2011 .

[27]  Xinghao Ding,et al.  Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal , 2016, IEEE Transactions on Image Processing.

[28]  Xiaochun Cao,et al.  Single Image Dehazing via Multi-scale Convolutional Neural Networks , 2016, ECCV.