Jensen-Generalized Discrete Fisher Information, Its Generating Function, and Applications to Image Processing and Contaminated Models
In this work, we first introduce a discrete version of generalized Fisher information measure and develop some new results for it. We then propose Jensen-generalized discrete Fisher (Jensen-GDF) information as a generalized measure, based on the convexity property of generalized discrete Fisher information measure. We further introduce generating functions for generalized discrete Fisher information and Jensen-GDF information measures and use them to develop some results. We also propose a new correlation coefficient in terms of the generalized discrete Fisher information and discuss some of its properties. Finally, to demonstrate the usefulness of the Jensen-generalized discrete Fisher information measure and the proposed correlation coefficient, we apply them to two real-world examples in image processing and forms of contaminated data, and present corresponding numerical results. Our findings show that the Jensen-GDF information measure and the correlation coefficient introduced here are effective criteria for quantifying similarity between two images in image processing settings and for analyzing contaminated data.
Authors
- Omid Kharazmi (ORCID: https://orcid.org/0000-0003-4176-9708)
- N. Balakrishnan (ORCID: https://orcid.org/0000-0001-5842-8892)
Institutions
- Vali Asr University of Rafsanjan (IR)
- McMaster University (CA)
Publication Details
- Journal
- IEEE Transactions on Information Theory
- Published
- 2025-09-09
- DOI
- https://doi.org/10.1109/tit.2025.3607695
- Primary Topic
- Advanced Statistical Methods and Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00