Single-image deraining using an adaptive nonlocal means filter

An adaptive rain streak removal algorithm for a single image is proposed in this work. We observe that a typical rain streak has an elongated elliptical shape with a vertical orientation. Thus, we first detect rain streak regions by analyzing the rotation angle and the aspect ratio of the elliptical kernel at each pixel location. We then perform the nonlocal means filtering on the detected rain streak regions by selecting nonlocal neighbor pixels and their weights adaptively. Experimental results demonstrate that the proposed algorithm removes rain streaks more efficiently and provides higher restored image qualities than conventional algorithms.

[1]  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.

[2]  Jean-Michel Morel,et al.  A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[3]  Shree K. Nayar,et al.  When does a camera see rain? , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[4]  Peyman Milanfar,et al.  Kernel Regression for Image Processing and Reconstruction , 2007, IEEE Transactions on Image Processing.

[5]  Hao Li,et al.  Rain Removal in Video by Combining Temporal and Chromatic Properties , 2006, 2006 IEEE International Conference on Multimedia and Expo.

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

[7]  Shree K. Nayar,et al.  Vision and Rain , 2007, International Journal of Computer Vision.

[8]  Shree K. Nayar,et al.  Detection and removal of rain from videos , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

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