In this research work, we introduced a novel subclass $ \mathcal{B}_{\lambda}^{\vartheta, \varsigma}(\alpha, \beta; y, \zeta) $ of bi-univalent functions associated with the Bell distribution by using Jacobi polynomials. For this class, coefficient bounds $ |a_2| $ and $ |a_3| $, together with the corresponding Fekete–Szegö inequality were obtained. Based on these theoretical results, a simple and effective image enhancement algorithm (BJBIEA) model was proposed using a novel convolution strategy implemented through a $ 3 \times 3 $ mask. The outcomes showed that the suggested method for general-purpose image enhancement is effective, dependable, and adaptable. The extension of this framework to detail enhancement, edge extraction, and image resolution quality will be the focus of future work.
Citation: Vanithakumari Balasubramaniam, Serkan Araci, Selvaraj Palanisamy. On certain subclasses of bi-univalent functions associated with Jacobi polynomials and the Bell distribution with applications to image enhancement[J]. AIMS Mathematics, 2026, 11(9): 32181-32198. doi: 10.3934/math.20261265
In this research work, we introduced a novel subclass $ \mathcal{B}_{\lambda}^{\vartheta, \varsigma}(\alpha, \beta; y, \zeta) $ of bi-univalent functions associated with the Bell distribution by using Jacobi polynomials. For this class, coefficient bounds $ |a_2| $ and $ |a_3| $, together with the corresponding Fekete–Szegö inequality were obtained. Based on these theoretical results, a simple and effective image enhancement algorithm (BJBIEA) model was proposed using a novel convolution strategy implemented through a $ 3 \times 3 $ mask. The outcomes showed that the suggested method for general-purpose image enhancement is effective, dependable, and adaptable. The extension of this framework to detail enhancement, edge extraction, and image resolution quality will be the focus of future work.
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