Free Spatially-Variant Deconvolution based on the Richardson-Lucy algorithm with total variation regularisation
A publication accompanying the code has been published in BOEx (open access)[1]:
Raphaël Turcotte, Eusebiu Sutu, Carla C. Schmidt, Nigel J. Emptage, Martin J. Booth.
"Deconvolution for multimode fiber imaging: modeling of spatially variant PSF",
Biomedical Optics Express 2020:11(8);4759-4771. DOI: 10.1364/BOE.399983
The repository contains the MATLAB codes requires to deconvolve a 2D image acquired with a system having a spatially variant point response. The deconvolution is based on a modified Richardson-Lucy algorithm with total variation regularisation to account for the spatially variant point response. Sample datasets are also provided.
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Code:
- RLTV_SVdeconv.m: Function performing Richardson-Lucy deconvolution with total variation (TV) regularisation using a spatially-variant PSF model based on eigen-PSF decomposition.
- TVL1reg.m: Function calculating the total variation regularisation factor for the RL algorithm using the L1 norm over the divergence of the array M
- ScriptLRTV.m: Sample script iteratively calling the RLTV_SVdeconv() function for the given inputs over several number of modes, number of iterations, and TV coefficient values.
- makeEdgeAtt.m: This function create a square array of amplitude 1 with the edges attenuated to zero using a cos function for a given number of pixels.
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Datasets:
- Illumination focal spot image from From Fig. 4 in ref [1].
- Bead image from From Fig. 5. in ref [1].