Laser & Optoelectronics Progress, Volume. 55, Issue 5, 051002(2018)
Contrast Adjustment Based on Image Retrieval
Fig. 1. Overall frameworkof algorithm
Fig. 2. Enhancement of context-sensitive and context-free. (a) Original image; (b) context-sensitive; (c) context-free
Fig. 3. Visual threshold and image background brightness curve
Fig. 4. (a) CLAHE transform after adaptive brightness equalize; (b) CLAHE transform
Fig. 5. Enhanced image with brightness adjustment module corresponding to different optimal solutions. (a) CLAHE as optimal solution; (b) CLAHE transform after brightness equalize as optimal solution
Fig. 6. Reference image and image to be enhanced and its quality score. (a)-(g) Reference images; (h)-(n) images to be enhanced
Fig. 7. Average score of subjective evaluation
Fig. 8. Average score of NIQE, NIQMC, clarity
Fig. 9. Weak contrast images treated by different methods. (a) Original image; (b) AGWD method; (c) BIQME method; (d) GICE method; (e) ROHIM method; (f) proposed method
Fig. 10. Dark image treated by diffeent methods. (a) Original image; (b) AGWD method; (c) BIQME method; (d) GICE method; (e) ROHIM method; (f) proposed method
Fig. 11. Night image treated by different methods. (a) Original image; (b) AGWD method; (c) BIQME method; (d) GICE method; (d) ROHIM method; (f) proposed method
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Yanjia Fei, Feng Shao. Contrast Adjustment Based on Image Retrieval[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051002
Category: Image processing
Received: Sep. 26, 2017
Accepted: --
Published Online: Sep. 11, 2018
The Author Email: Shao Feng (shaofeng@nbu.edu.cn)