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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2019 Vol.20 No.2 P.206-221
Automatic image enhancement by learning adaptive patch selection
Abstract: Today, digital cameras are widely used in taking photos. However, some photos lack detail and need enhancement. Many existing image enhancement algorithms are patch based and the patch size is always fixed throughout the image. Users must tune the patch size to obtain the appropriate enhancement. In this study, we propose an automatic image enhancement method based on adaptive patch selection using both dark and bright channels. The double channels enhance images with various exposure problems. The patch size used for channel extraction is selected automatically by thresholding a contrast feature, which is learned systematically from a set of natural images crawled from the web. Our proposed method can automatically enhance foggy or under-exposed/backlit images without any user interaction. Experimental results demonstrate that our method can provide a significant improvement in existing patch-based image enhancement algorithms.
Key words: Image enhancement, Contrast enhancement, Dark channel, Bright channel, Adaptive patch based processing
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DOI:
10.1631/FITEE.1700125
CLC number:
TP391.4
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On-line Access:
2024-08-27
Received:
2023-10-17
Revision Accepted:
2024-05-08
Crosschecked:
2019-01-22