Laser & Optoelectronics Progress, Volume. 57, Issue 20, 201020(2020)
Dunhuang Mural Inpainting Algorithm Based on Sequential Similarity Detection and Cuckoo Optimization
Figures & Tables(12)
Fig. 2. Changes in various data during mural restoration. (a) Mask image; (b) change in confidence; (c) change in date item; (d) change in priority
Fig. 3. Restoration effect of images at each threshold. (a)Original image; (b)mask image; (c) Yth=10000; (d) Yth=5000; (e) Yth=2000; (f) Yth=1000; (g) Yth=500; (h) Yth=200; (i) Yth=50; (j) dynamic threshold of proposed method
Fig. 4. Restoration results of mural 1. (a) Original image; (b) mask image; (c) traditional Criminisi method; (d) method in Ref.[9]; (e) method in Ref.[11] ; (f) proposed method; (g) enlarged restored area of traditional Criminisi method; (h) enlarged restored area of method in Ref.[9]; (i) enlarged restored area of method in Ref.[11];(j) enlarged restored area of proposed method
Fig. 5. Restoration results of mural 2. (a) Original image; (b) mask image; (c) Criminisi method; (d) method in Ref.[9];(e) method in Ref.[11]; (f) proposed method
Fig. 6. Restoration results of mural 3. (a) Original image; (b) mask image; (c) Criminisi method; (d) method in Ref.[9];(e) method in Ref.[11]; (f) proposed method
Fig. 7. Restoration results of mural 4. (a) Original image; (b) mask image; (c) traditional Criminisi method; (d) method in Ref.[9]; (e) method in Ref.[11]; (f) proposed method; (g) enlarged restored area of traditional Criminisi method; (h) enlarged restored area of method in Ref.[9]; (i) enlarged restored area of method in Ref.[11]; (j) enlarged restored area of proposed method
Fig. 8. Mural restoration results in large areas. (a) Original image; (b) mask image; (c) Criminisi method; (d) method in Ref.[9]; (e) method in Ref.[11]; (f) proposed method
Fig. 9. Mural restoration results in real damaged areas. (a) Original images; (b) mask images; (c) Criminisi method; (d) method in Ref.[9]; (e) method in Ref.[11]; (f) proposed method
Table 1. PSNR and time under different methods
View tableTable 1. PSNR and time under different methods
Method SSDA with fixed threshold Proposed method 10000 5000 2000 1000 500 200 50 PSNR /dB 32.56 33.71 32.82 33.76 33.69 32.20 32.09 36.68 Time /s 8.65 8.28 8.04 7.19 6.90 6.37 5.80 6.26
Table 2. PSNR values of restoration results of each algorithmunit: dB
View tableTable 2. PSNR values of restoration results of each algorithmunit: dB
No. Mask image Criminisi method Method in Ref.[9] Method in Ref.[11] Proposed method 1 22.1686 32.8772 35.2642 35.9254 37.1888 2 24.6271 33.0012 34.1628 33.0956 35.0714 3 26.5476 37.1448 40.4067 39.2145 41.9898 4 34.3625 40.3273 43.4216 41.8620 43.5608 5 30.2568 37.2985 39.9856 38.7564 40.0258 6 26.2545 30.1698 32.4183 32.4215 32.6986 7 25.6589 30.5896 31.5244 30.9896 31.8652 8 23.2546 29.3256 29.1589 29.3624 30.0526 9 32.2568 39.5428 41.0269 40.1563 42.0024 10 21.2351 33.4585 34.5624 34.8024 34.8569
Table 3. Restoration time of each algorithm unit: s
View tableTable 3. Restoration time of each algorithm unit: s
No. Criminisi method Method in Ref.[9] Method in Ref.[11] Proposed method 1 2 664.5629 395.1932 557.4610 346.5987 541.3256 322.7564 376.2413 284.8241
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Yong Chen, Jin Chen, Yapeng Ai, Meifeng Tao. Dunhuang Mural Inpainting Algorithm Based on Sequential Similarity Detection and Cuckoo Optimization[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201020
Paper Information
Category: Image Processing
Received: Jan. 13, 2020
Accepted: Feb. 24, 2020
Published Online: Oct. 17, 2020
The Author Email: Chen Yong (edukeylab@126.com)
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