Presentation + Paper
21 April 2020 Extended retinex and optimized image sharpening for hidden detail uncovering, visual range improvement, and image enhancement
Author Affiliations +
Abstract
Camera images often contain more information than the human eye can notice. Despite numerous influences degrading image quality, there is potentially some information present or there are at least traces in the image data which would be interesting to be examined but which are below a recognition threshold. And quite often hard to see information needs to be extracted from degraded images or image parts. This paper focuses on making such information visible. First, a novel dedicated retinex algorithm uncovers hidden details due to low contrast. Unlike other retinex variants, it does not only improve the contrast in dark image regions but at any grayvalue or color level. Additionally, it avoids halo effects to a high degree. Second, a dedicated image sharpening method uncovers hidden details due to blurring or haziness and clarifies washed-out details. In comparison to known methods this is done more effectively while image noise and compression artifacts are significantly less increased. Both proposed image enhancement methods are easy to implement. The given results show them to be powerful to uncover image details and to increase the amount of obtained visualized information, which eventually improves the visual range of the camera.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Müller "Extended retinex and optimized image sharpening for hidden detail uncovering, visual range improvement, and image enhancement", Proc. SPIE 11396, Computational Imaging V, 113960A (21 April 2020); https://doi.org/10.1117/12.2558699
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KEYWORDS
Image enhancement

Image filtering

Visualization

Convolution

Electronic filtering

Image compression

Image contrast enhancement

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