Abstract
We propose modifications of the Richardson–Lucy iterations (RL) and the Image Space Reconstruction Algorithm (ISRA) that demonstrate accelerated convergence and lead to improved image restoration results. We show that the iterations of RL, ISRA, and the proposed modifications can be interpreted as fixed-point iterations corresponding to the minimizers of certain variational problems. We demonstrate that combining each iteration of the proposed modifications with an adaptive image smoothing procedure leads to substantial improvements of the image restoration results. An implementation is available at https://github.com/fayolle/Mult_BBDeblur_demo.
Original language | English |
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Article number | 109910 |
Journal | Signal Processing |
Volume | 232 |
Early online date | 3 Feb 2025 |
DOIs | |
Publication status | E-pub ahead of print - 3 Feb 2025 |
Keywords
- Accelerated and enhanced RL and ISRA
- Image deblurring
- Variational image deconvolution
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering