ArticleScientific reports2026
Miller-Ross-functions coefficients and kernel-based CT-scan enhancement technique.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Miller-Ross-functions coefficients and kernel-based CT-scan enhancement technique.Scientific reports · 2026Article
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Abstract
In Digital Image Processing (DIP), image enhancement using univalent functions entails mapping pixel intensity values (gray levels) using one-to-one, invertible complex functions, frequently in the frequency domain or through specialized transformations, to stretch, compress, or redistribute intensities for improved visual quality or feature detection, such as boosting contrast or lowering noise, by making sure each input pixel maps uniquely to an output pixel, going beyond simple linear/non-linear transforms. In this paper, for the new subclasses [Formula: see text] and [Formula: see text] of [Formula: see text] in association with normalized form of Miller-Ross-type functions explored and the key coefficient inequality as given below [Formula: see text]where [Formula: see text] [Formula: see text] is considered. By suitably fixing the parameters ϱ and ϖ, in [Formula: see text] and using these coefficients we discuss their application to enhance medical images in image processing. Furthermore, we introduce a novel image sharpening methodology that leverages coefficient bounds derived from the Miller-Ross function with fixing the parameters ϱ and ϖ values, integrating these bounds into pre-processing strategies for enhancing medical CT images.
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