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Deconvolution is an image restoration technique which improves image contrast, resolution and signal to noise ratio. In modern optical microscopy and biological research deconvolution is becoming a fundamental processing step which allows for better image analysis. Deconvolution remains however a challenging task as the result depends strongly on the algorithm chosen, the parameters settings and the kinds of structures in the processed dataset. As a core facility of bio-imaging and microscopy, we aim with this study to compare the performances of different deconvolution software. In this first part of our survey we present deconvolution related problems, we introduce software we took into account, and we provide the complete dataset we produced for software testing and a PSF generator. A second part will follow the present one. In the second part we will highlight advantages and weak points of tested software by the statement of the performed tests.
Edoardo Charbon, Claudio Bruschini