Low light enhancement algorithm for color images using intuitionistic fuzzy sets with histogram equalization

• Published in: Multimedia tools and applications Vol. 81; no. 6; pp. 8093 - 8106
• Main Authors: Jebadass, J. Reegan, Balasubramaniam, P.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2022; Springer Nature B.V
• Subjects: Algorithms; Color imagery; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Discrete cosine transform; Equalization; Fuzzy logic; Fuzzy sets; Histograms; Image enhancement; Image quality; Multimedia Information Systems; Special Purpose and Application-Based Systems; Intuitionistic fuzzy sets; Image enhancement; Histogram equalization
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-022-12087-9

In this work, a new fuzzy logic-based algorithm is proposed for the enhancement of low light color images. A generalization of a fuzzy set known as an intuitionistic fuzzy set (IFS) is used in this paper, which expresses the evidence of the support, opposition, and hesitation simultaneously. To generate non-membership degrees, Yager’s generating function is used. Again entropy formula is used to generate non-membership degrees for improving the quality of the enhanced image derived by the proposed method. In the experimental section, the proposed method is compared with other existing methods like histogram equalization, contrast limited adaptive histogram equalization, histogram specification approach, discrete cosine transform coefficient, brightness preserving dynamic fuzzy histogram equalization, and intuitionistic fuzzy image. The experimental results revealed that the proposed method gives better results than the other existing methods. Performances are evaluated using entropy and structural similarity index. A comparative analysis of the quality of enhanced images shows that the proposed method performs better than several existing methods.