NDLI: Restoration algorithm for noisy complex illumination

Content Provider	IET Digital Library
Author	Liu, Zhanwen Gao, Tao Kong, Fanjie Jiao, Ziheng Yang, Aodong Li, Shuying Liu, Bo
Abstract	Although promising results have been achieved in the restoration of complex illumination images with the Retinex algorithm, there are still some drawbacks in the processing of Retinex. Considering the noise characteristics of complex illumination images, in this study, we propose a novel restoration algorithm for noisy complex illumination, which combines guided adaptive multi-scale Retinex (GAMSR) and improvement BayesShrink threshold filtering (IBTF) based on double-density dual-tree complex wavelet transform (DDDTCWT) domain. Extensive restoration experiments are conducted on three typical types images and the same image with different noises. On the basis of a series of evaluation indexes, we compare our method to those of state-of-the-art algorithms. The results show that (i) SSIM of the proposed IBTF is superior to traditional Bayes threshold method by 15% as the standard variance is 100. (ii) PSNR of the proposed GAMSR enhances 15% to traditional MSR. (iii) The clarity of final results for restoration speeds up three times than that of original images, and the information entropy is improved slightly too. Therefore, the proposed method can effectively enhance the details, edges and textures of the image under complex illumination and noises.
Starting Page	224
Ending Page	232
Page Count	9
ISSN	17519632
Volume Number	13
e-ISSN	17519640
Issue Number	Issue 2, Mar (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/13/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2018.5163
Journal	IET Computer Vision
Publisher Date	2018-08-09
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bayes Method Bayes Threshold Method BayesShrink Threshold Filtering Combinatorial Mathematics Complex Illumination Image Restoration Computer Vision And Image Processing Technique DDDTCWT Domain Double-density Dual-tree Complex Wavelet Transform Domain Entropy Evaluation Indexes Filtering Method in Signal Processing GAMSR Guided Adaptive Multiscale Retinex Algorithm High-frequency Subband IBTF Image Filtering Image Processing Image Restoration Information Entropy Integral Transforms Inverse Transforms Inverse WT Low-frequency Subband Mathematics Noisy Complex Illumination Object Detection Optical, Image And Video Signal Processing Peak Signal-to-noise Ratio PSNR Restoration Algorithm SSIM Statistics Structural Similarity Trees Wavelet Transform
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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