›› 2012, Vol. ›› Issue (06): 1592-1596.

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Retinex enhancement method of multi-exposure workpiece images based on NSCT

LI Ao1, LI Yi-bing1, LIU Dan-dan2, YANG Xiao-dong1   

  1. 1. Institute of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China;
    2. Modern Manufacture Engineering Center, Heilongjiang Institute of Science and Technology, Harbin 150001, China
  • Received:2011-09-29 Online:2012-11-01

Abstract: To overcome the problems in muti-exposure workpiece images, such as Low Dynamic Range (LDR), more reflective surfaces and excessive saturation, we propose a method of Retinex for enhancing the LDR image order, which extends the processing of Retinex on single image to image sequence and synthesizes the information from each image in the sequence. Introducing the illumination model, the proposed method solves the drawback that the traditional algorithm did not consider the influences of the illumination condition and the exposure time sufficiently. In addition, for protecting the edge, we decompose the approximate and detail components by the Nonsubsampled Contourlet Transform (NSCT), which has the band-pass character with multi-direction. Meanwhile, we separate the illumination and reflection components from the low approximate sub-image and select the optimal component combination. The results show that our proposed method not only removes the super-saturation of some reflective panels, but also promotes the visual dynamic range availably.

Key words: information processing technology, image enhancement, multi-exposure images, non-subsampled contourlet, Retinex

CLC Number: 

  • TN911.73
[1] Meylan L, Süsstrunk S. High dynamic range image rendering with a Retinex-based adaptive filter[J]. IEEE Transaction on Image Processing, 2006,15(9):2820-2830.
[2] Jung J, Park H, Kang S, et al. Measurement of initial motion of a flying golf ball with multi-exposure image for screen-golf[J]. IEEE Trans on Consumer Electronics,2010,52(2):516-523.
[3] 李洪兵,余成波,张冬梅,等. 基于脊波变换的手指静脉图像增强研究[J]. 重庆邮电大学学报:自然科学版,2011,23(2):224-230. Li Hong-bing,Yu Cheng-bo,Zhang Dong-mei,et al. Study on finger vein image enhancement based on ridgelet transformation[J].Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2011,23(2):224-230.
[4] Edwin Land. The Retinex theory of color vision[J]. Seientific Ameriea, 1977,237 (6):108-129.
[5] Ahmed A M T. Automatic color retrieval using the Retinex and its max white intrinsic property[C]//The 7th International Conference on Informatics and Systems, Cairo, Egypt,2010:1-5.
[6] Xiong W H, Funt B. Stereo retinex[J]. Image and Vision Computing,2009,27(1/2):178-188.
[7] Nayar S K, Mitsunaga T. High dynamic range imaging spatially varying pixel exposures[C]//IEEE Conference on Computer Vision and Pattern Recognition, USA, 2000,1:472-479.
[8] 张丽芳,周军. 利用多曝光对图像进行动态范围增强[J].数据采集与处理,2007,22(4):417-422. Zhang Li-fang, Zhou Jun. Dynamic range enhancement using multi-exposed images[J]. Journal of Data Acquisition & Processing,2007,22(4):417-422.
[9] Mertens T, Kautz J, Van Reeth F. Exposure fusion: A simple and practical alternative to high dynamic range photography[J]. Computer Graphics Forum, 2009,28(1): 161-171.
[10] Lee T H, Ha Ho-Gun, Ha Y H. Adaptive color enhancement based on multi-scaled Retinex using local contrast of the input image[C]//International Symposium on Optomechatronic Technologies, Toronto,2010:1-6.
[11] Jang I S, Park K H. Color correction by estimation of dominant chromaticity in g-scaled retinex[J]. Journal of Image Science and Technology, 2009, 53(5):1-11.
[12] Do M N, Vetterli M. The contourlet transform: an efficient directional multiresolution image representation[J]. IEEE Transaction on Image Processing, 2005, 14(12):2091-2106.
[13] Cunha A L, Zhou Jian-ping, Do M N. The nonsubsampled contourlet transform:theory, design, and applications[J]. IEEE Trans. On Image Processing, 2006, 15(10):3089-3101.
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