Dongbin Liu, Huiqin Wang, Ke Wang, Zhan Wang, Gang Zhen. Blind Restoration Method for Incomplete and Sparse Text Images Based on Content Style Transfer[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2411001
- Laser & Optoelectronics Progress
- Vol. 59, Issue 24, 2411001 (2022)
Fig. 1. Schematic of GAN
Fig. 2. Structure diagram of blind restoration network for incomplete sparse text image
Fig. 3. Max pooling diagram
Fig. 4. ISA mechanism diagram
Fig. 5. Generator network structure based on improved self-attention
Fig. 6. Discriminator network structure based on improved self-attention mechanism
Fig. 7. Partial incomplete characters in Tianjin dule Temple
Fig. 8. Segmentation results of incomplete text in Tianjin dule Temple
Fig. 9. Some regular script data of Ouyang xun, Wang Xizhi, Su Shi, Huang Tingjian, etc
Fig. 10. Comparison of experimental results. (a) Broken images; (b) CycleGAN; (c) CycleGAN (LS+SA); (d) proposed algorithm;(e) original images
Fig. 11. “Xi” “Du” “Nian” and “Huai” calligraphy image AHE. (a) “Xi”calligraphy image AHE; (b) “Du” calligraphy image AHE; (c) “Nian” calligraphy image AHE; (d) “Huai” calligraphy image AHE
Fig. 12. Image preprocessing results. (a) Original images; (b) AHE+SR; (c) text extraction
Fig. 13. Comparison results of different repair algorithms.(a) Adding mask artificially; (b) RFR; (c) proposed algorithm
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Table 1. PSNR, SSIM, and RMSE comparison results
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Table 2. Comparison results of PSNR, SSIM, and RMSE under various failure ratios
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Table 3. CCIR500-1 Subjective evaluation scale
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Table 4. Subjective evaluation results
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