Revealing Shadows: Low-Light Image Enhancement Using Self-Calibrated
  Illumination
Farzaneh Koohestani Nader Karimi Shadrokh Samavi
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.