Fractional diffusion model for removing additive noise with forward-backward diffusivity
Monika Ranireachmonika11@gmail.comDepartment of Mathematics & Data ScienceSharda School of Engineering & ScienceSharda UniversityGreater Noida, Uttar Pradesh, 201310, IndiaView full profile → , *Santosh KumarCorresponding authorskykumar87@gmail.comDepartment of Mathematics & Data ScienceSharda School of Engineering & ScienceSharda UniversityGreater Noida, Uttar Pradesh, 201310, India0000-0001-9500-7229View full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Dec 2025
- Published Online:
- 30 Sep 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIM-2663
- Pages:
- 2711–2720
Abstract
The PDE-based diffusion model is very effective in reducing noise and preserving edges, which are the major problems in image processing. This paper aims to propose a time-fractional diffusion model to remove additive noise from noisy images while keeping important edges clear. The proposed model uses both spatial derivatives and a time-fractional derivative. This fractional order helps control the diffusion process more effectively than the classical model. The model is discretized using a finite difference method for numerical implementation. The outcomes of the fractional model are evaluated using peak signal-to- noise ratio (PSNR), and the results show that the model improves noise removal while preserving image edges.
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References
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