Improved MSR Model for Image Enhancement in Different Color Spaces
DOI:
https://doi.org/10.54097/j2ngjx98Keywords:
Low-light, Multi-Scale Retinex, Gradient-domain Guided Filtering, Color SpaceAbstract
During the process of low-light image enhancement, the classic Multi-Scale Retinex (MSR) suffers from halo effects and insufficient color protection. Therefore, this paper proposes an improved MSR model. The core idea of this paper is to replace the Gaussian filter in MSR with gradient-domain guided filtering. Meanwhile, in the process of image enhancement, the differences among various color spaces are taken into account. Experiments have proven that the improved method proposed in this paper can effectively improve the quality of low-light images. However, when applying the proposed method to different color spaces, the experimental results do not confirm the existence of a universal optimal color space model. In the field of image enhancement, it is still necessary to choose the appropriate color space model according to the characteristics of the specific application scenario.
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[1] Cai R, Chen Z. Brain-like retinex: A biologically plausible retinex algorithm for low-light image enhancement [J]. Pattern Recognition, 2023.
[2] Ji K, Lei W, Zhang W. A deep retinex network for underwater low-light image enhancement [J]. Machine Vision and Applications, 2023, 34(6): 122.
[3] Shi X , Chen S , Huang F ,et al.Image restoration of luminous objects in dense fog[J].Optik - International Journal for Light and Electron Optics, 2022, 271(000):10.
[4] Land E H. The retinex theory of color vision [J]. Scientific American, 1978, 237(6): 108-128.
[5] Jobson D J, Rahman Z U, Woodell G A. Properties and performance of a center/surround retinex [J]. IEEE Transactions on Image Processing, 1997, 6(3): 451-462.
[6] Petro A B, Sbert C, Morel J M. Multiscale retinex [J/OL]. Image Processing On Line, 2014.
[7] Li X Y, Lu J J, Hao X L. An improved Retinex mine image enhancement algorithm [J]. Science Technology and Engineering, 2020, 20(29): 12028-12034.
[8] Wang H R, Zhang L, Wang J, et al. Research on underwater image enhancement algorithm based on improved homomorphic filtering and Retinex [J]. Electronics Optics & Control, 2021, 28(5): 32-35.
[9] Zhuang P , Li C , Wu J .Bayesian retinex underwater image enhancement[J].Engineering Applications of Artificial Intelligence, 2021, 101(1):104171.
[10] Song C Y, Shao Q. Research on Retinex defogging algorithm based on dark channel prior [J]. Software Guide, 2021, 20(S1): 214-218.
[11] Limare N, Lisani J L, Morel J M, et al. Simplest color balance [J/OL]. Image Processing On Line, 2011, 1.
[12] Kou F, Chen W, Wen C, et al. Gradient domain guided image filtering [J]. IEEE Transactions on Image Processing, 2015, 24(11): 4528-4539.
[13] Froment J. Parameter-free fast pixel wise non-local means denoising [J/OL]. Image Processing On Line, 2014, 4: 300-326.
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