Efficient low-light image enhancement via balancing polynomials-based adaptive contrast control using coefficient inequalities of a subclass of bi-univalent functions
AIMS MATHEMATICS, cilt.11, sa.10, ss.32394-32408, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 11 Sayı: 10
- Basım Tarihi: 2026
- Doi Numarası: 10.3934/math.20261273
- Dergi Adı: AIMS MATHEMATICS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.32394-32408
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Bursa Uludağ Üniversitesi Adresli: Evet
Özet
In this research work, we introduced a novel subclass of bi-univalent functions associated with balancing polynomials. For this class, we derived coefficient estimates |alpha 2|, |alpha 3| along with Fekete-Szego & uml; inequalities. Motivated by these theoretical findings, we proposed a new model based on balancing polynomials. The proposed low-light enhancement model consists of gamma correction and adaptive polynomial components, which make the image brighter without losing details. To avoid over-enhancement, a control mechanism based on the contrast improvement index (CII) was adopted to ensure that the performance is the same in different lighting situations. According to tests on a number of low-light images, the proposed method had higher entropy with controlled contrast than other traditional methods. By maintaining a consistent balance between detail enhancement and natural visual appearance, the technique validated its effectiveness and appropriateness for practical image-enhancement applications.