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Color image enhancement technique based on interval-valued intuitionistic fuzzy set

Authors:

J. Reegan Jebadass,

P. BalasubramaniamAuthors Info & Claims

Volume 653, Issue C

https://doi.org/10.1016/j.ins.2023.119811

Published: 01 January 2024 Publication History

Abstract

In this paper, a new interval-valued intuitionistic fuzzy-based algorithm is proposed to enhance low-light images. In this proposed algorithm, the low-light image is first changed to the fuzzy image by normal fuzzification. Then the above is converted to an intuitionistic fuzzy image and further to the interval-valued intuitionistic fuzzy image. After applying contrast limited adaptive histogram equalization, we derive the required image. In the experimental part, the proposed algorithm is compared with other existing algorithms including histogram equalization, contrast limited adaptive histogram equalization, histogram specification, dehazing, fractional order image enhancement, intuitionistic fuzzy, and interval-valued intuitionistic fuzzy. In terms of overall visual quality and performance metrics, the results showed that the proposed technique surpasses other current methods including entropy, absolute mean brightness error, and contrast improvement index.

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Digital Library

Cited By

Ramesh Babu NSam Joshua ABalasubramaniam PTiwari A(2024)Fuzzy-driven image enhancement via ABR-fractal-fractional differentiationInformation Sciences: an International Journal10.1016/j.ins.2024.120741675:COnline publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1016/j.ins.2024.120741

Index Terms

Color image enhancement technique based on interval-valued intuitionistic fuzzy set
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
    2. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic
  2. Computer graphics
    1. Image manipulation

Index terms have been assigned to the content through auto-classification.

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cover image Information Sciences: an International Journal

Information Sciences: an International Journal Volume 653, Issue C

Jan 2024

602 pages

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Elsevier Inc.

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Elsevier Science Inc.

United States

Publication History

Published: 01 January 2024

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Cited By

Ramesh Babu NSam Joshua ABalasubramaniam PTiwari A(2024)Fuzzy-driven image enhancement via ABR-fractal-fractional differentiationInformation Sciences: an International Journal10.1016/j.ins.2024.120741675:COnline publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1016/j.ins.2024.120741

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