Enhancing colour image contrast via analytic functions subordinate to generalized Mersenne polynomials
B. Aarthy, B. Srutha Keerthi · The Imaging Science Journal · 2025
Digitally captured and transferred colour images often suffer from low contrast, impacting both human perception and automated system performance. To address this issue with minimal information loss, we propose a new contrast enhancement method using a transformation function derived from Sakaguchi type functions subordinate to Generalized Mersenne polynomials on the open unit disk. This pixel-wise transformation enhances image intensity and contrast effectively. The method is particularly well-suited for colour images, producing high-quality outputs while preserving image details. Its simplicity allows application across various image types with varying contrast degradation. We evaluate our approach on 275 low-contrast images from two datasets - Categorical Image Quality (CSIQ) Database and Tampere Image Database (TID2013) - across five distortion levels. Also, a comparative study with other state-of-the-art techniques demonstrates that the proposed method achieves superior visual quality.