2023/12/23 by Farzaneh Koohestani, Nader Karimi, Koohestani, Farzaneh +3
Computer Science · Physics and Astronomy · #Advanced Vision and Imaging #Color Science and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image Enhancement Techniques #Image and Video Processing (eess.IV) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2312.15199
openalex publication_date 2023/12/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In digital imaging, enhancing visual content in poorly lit environments is a significant challenge, as images often suffer from inadequate brightness, hidden details, and an overall reduction in quality. This issue is especially critical in applications like nighttime surveillance, astrophotography, and low-light videography, where clear and detailed visual information is crucial. Our research addresses this problem by enhancing the illumination aspect of dark images. We have advanced past techniques by using varied color spaces to extract the illumination component, enhance it, and then recombine it with the other components of the image. By employing the Self-Calibrated Illumination (SCI) method, a strategy initially developed for RGB images, we effectively intensify and clarify details that are typically lost in low-light conditions. This method of selective illumination enhancement leaves the color information intact, thus preserving the color integrity of the image. Crucially, our method eliminates the need for paired images, making it suitable for situations where they are unavailable. Implementing the modified SCI technique represents a substantial shift from traditional methods, providing a refined and potent solution for low-light image enhancement. Our approach sets the stage for more complex image processing techniques and extends the range of possible real-world applications where accurate color representation and improved visibility are essential.