Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0410004(2021)
Adaptive Image Defogging Algorithm Combining Multi-Scale Retinex and Dark Channel
Figures & Tables(9)
![Transmittance images after processing by different methods. (a) Hazy images; (b) Ref. [8]; (c) rough estimations of transmittance; (d) transmittance optimization](/Images/icon/loading.gif){kind=icon}
Fig. 2. Transmittance images after processing by different methods. (a) Hazy images; (b) Ref. [8]; (c) rough estimations of transmittance; (d) transmittance optimization
Fig. 3. Effect of different algorithms for processing close-range images. (a) Original images; (b) Ref. [7]; (c) Ref. [8]; (d) Ref. [9]; (e) Ref. [12]; (f) proposed algorithm
Fig. 4. Effect of different algorithms for processing alternating near-and-far images. (a) Original images; (b) Ref. [7]; (c) Ref. [8]; (d) Ref. [9]; (e) Ref. [12]; (f) proposed algorithm
Fig. 5. Effect of different algorithms for processing perspective images. (a) Original images; (b) Ref. [7]; (c) Ref. [8]; (d) Ref. [9]; (e) Ref. [12]; (f) proposed algorithm
Table 1. p values of processing different images by different algorithms
View tableTable 1. p values of processing different images by different algorithms
Image Ref. [7] Ref. [8] Ref. [9] Ref. [12] Proposed
algorithm1 0.0997 0.0867 0.0318 0.0148 0.1143 2 0.2492 0.2994 0.1021 0.1775 0.4928 3 0.3485 0.3967 -0.0021 0.1280 0.3821 4 0.3115 0.1456 -0.0789 0.0553 0.2071 5 0.0852 -0.0266 -0.1392 0.0849 0.1729 6 0.1451 0.0823 -0.0070 0.0627 0.1423 7 -0.0350 -0.0150 -0.2082 0.0412 0.1095 Mean 0.1720 0.1384 -0.0431 0.0806 0.2316
Table 2. t values of processing different images by different algorithms
View tableTable 2. t values of processing different images by different algorithms
Image Ref. [7] Ref. [8] Ref. [9] Ref. [12] Proposed
algorithm1 1.2296 1.1788 1.0159 1.0657 1.3386 2 1.1138 1.1596 1.0685 1.2269 1.6675 3 1.1859 1.1761 1.1169 1.1751 1.5083 4 1.1104 1.0774 0.9077 1.1679 1.6777 5 1.1814 1.0341 0.8125 1.1625 1.5929 6 1.1371 1.0750 1.0229 1.1397 1.3475 7 1.0939 1.1230 0.9799 1.1159 1.8649 Mean 1.1503 1.1177 0.9892 1.1505 1.5711
Table 3. PSNR of processing different images by different algorithms
View tableTable 3. PSNR of processing different images by different algorithms
Image Ref. [7] Ref. [8] Ref. [9] Ref. [12] Proposed algorithm 1 61.2513 61.4723 62.1003 65.6993 62.1086 2 55.8298 57.0069 58.6501 58.6995 63.4518 3 58.0261 58.0033 61.2204 64.6648 61.8904 4 59.1774 55.5100 60.1118 65.4617 63.4308 5 60.9005 59.6184 61.0325 67.0162 62.3975 6 60.5424 59.5899 61.4846 68.1238 63.3756 7 59.0992 60.1070 61.4118 66.0904 60.2116 Mean 59.2610 58.7583 60.8588 65.1080 62.4095
Table 4. Running time of processing different images by different algorithms unit: s
View tableTable 4. Running time of processing different images by different algorithms unit: s
Image Ref. [7] Ref. [8] Ref. [9] Ref. [12] Proposed algorithm 1 0.5069 0.0932 2.5809 1.5018 1.1069 2 1.1512 0.0841 2.2040 1.7727 1.1731 3 0.5956 0.2506 1.4160 3.8809 2.3102 4 0.4769 0.1391 1.5732 1.9901 1.2699 5 0.4351 0.0484 1.6150 0.7655 0.7919 6 0.4399 0.0864 1.9004 1.3791 1.0923 7 0.4036 0.0580 1.0559 0.6043 0.5253 Mean 0.5727 0.1085 1.7636 1.6992 1.1814
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Jing Peng, Fengjin Xue, Yubin Yuan. Adaptive Image Defogging Algorithm Combining Multi-Scale Retinex and Dark Channel[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410004
Paper Information
Category: Image Processing
Received: Jun. 28, 2020
Accepted: Aug. 3, 2020
Published Online: Feb. 8, 2021
The Author Email: Xue Fengjin (459677370@qq.com)
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