A novel Retinex based enhancement algorithm considering noise

The traditional center/surround Retinex enhancement algorithms only consider the illuminance. So it may amplify the noise. However image details will be lost in the subsequent denoising process. In this paper, we propose an illuminance-reflectance model(IRMNE) which can denoise the image taken in the low light and enhance it at the same time. IRMNE can overcome the limitations of traditional algorithms. The experiment results indicate the validity and advantage of our algorithm. Compared with other algorithms, IRMNE makes a better balance between image enhancement and image denoising, which helps to get more reliable color restoration results.

[1]  Zia-ur Rahman,et al.  A multiscale retinex for bridging the gap between color images and the human observation of scenes , 1997, IEEE Trans. Image Process..

[2]  G. Buchsbaum A spatial processor model for object colour perception , 1980 .

[3]  Michael L. Honig,et al.  Adaptive reduced-rank interference suppression based on the multistage Wiener filter , 2002, IEEE Trans. Commun..

[4]  Gérard G. Medioni,et al.  Perceptually motivated automatic sharpness enhancement using hierarchy of non-local means , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[5]  Laurence Meylan,et al.  High dynamic range image rendering with a retinex-based adaptive filter , 2006, IEEE Transactions on Image Processing.

[6]  Aggelos K. Katsaggelos,et al.  Simultaneous multichannel image restoration and estimation of the regularization parameters , 1997, IEEE Trans. Image Process..

[7]  Jian Sun,et al.  Guided Image Filtering , 2010, ECCV.

[8]  Yair Weiss,et al.  Scale invariance and noise in natural images , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[9]  Bo Li,et al.  Image enhancement based on Retinex and lightness decomposition , 2011, 2011 18th IEEE International Conference on Image Processing.

[10]  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).

[11]  Ming-rong Wang,et al.  Image enhancement algorithm combining multi-scale Retinex and bilateral filter , 2015 .

[12]  Siwei Luo,et al.  A novel visual perception enhancement algorithm for high-speed railway in the low light condition , 2014, 2014 12th International Conference on Signal Processing (ICSP).

[13]  Mario Bertero,et al.  Introduction to Inverse Problems in Imaging , 1998 .

[14]  Zhiguo Jiang,et al.  No Reference Uneven Illumination Assessment for Dermoscopy Images , 2015, IEEE Signal Processing Letters.

[15]  E. Land,et al.  Lightness and retinex theory. , 1971, Journal of the Optical Society of America.

[16]  Byung Cheol Song,et al.  Power-Constrained Contrast Enhancement Algorithm Using Multiscale Retinex for OLED Display , 2014, IEEE Transactions on Image Processing.

[17]  Zia-ur Rahman,et al.  Properties and performance of a center/surround retinex , 1997, IEEE Trans. Image Process..

[18]  Jean-Michel Morel,et al.  A PDE Formalization of Retinex Theory , 2010, IEEE Transactions on Image Processing.

[19]  Vijayan K. Asari,et al.  Design of a Digital Architecture for Real-Time Video, Enhancement Based on Illuminance-Reflectance Model , 2006, 2006 49th IEEE International Midwest Symposium on Circuits and Systems.

[20]  E H Land,et al.  An alternative technique for the computation of the designator in the retinex theory of color vision. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Sos S. Agaian,et al.  Fast Fourier transform-based Retinex and alpha-rooting color image enhancement , 2015, Commercial + Scientific Sensing and Imaging.

[22]  Giovanni Ramponi,et al.  High Dynamic Range Image Display With Halo and Clipping Prevention , 2011, IEEE Transactions on Image Processing.

[23]  Alessandro Rizzi,et al.  Random Spray Retinex: A New Retinex Implementation to Investigate the Local Properties of the Model , 2007, IEEE Transactions on Image Processing.

[24]  Michael Elad,et al.  A Variational Framework for Retinex , 2002, IS&T/SPIE Electronic Imaging.

[25]  Bo Jiang,et al.  Novel multi-scale retinex with color restoration on graphics processing unit , 2014, Journal of Real-Time Image Processing.

[26]  Vijayan K. Asari,et al.  An Illuminance-Reflectance Model for Nonlinear Enhancement of Color Images , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[27]  Zia-ur Rahman,et al.  Statistics of visual representation , 2002, SPIE Defense + Commercial Sensing.