Multiplane Image Restoration Using Multivariate Curve Resolution: An Alternative Approach to Deconvolution in Conventional Brightfield Microscopy

Three-dimensional reconstruction in brightfield microscopy is challenging since a 2D image includes from in-focus and out-of-focus light which removes the details of specimen’s structures. To overcome this problem, many techniques exist, but these generally require an appropriate model Point Spread Function (PSF). Here, we propose new images restoration method based on application Multivariate Curve Resolution (MCR) algorithms to stack achieve 3D without need for PSF. The statistical approach using self-modelling mixture analysis. MCR-ALS (ALS Alternating Least Square) algorithm under non-negativity constraints, Wiener, Richardson–Lucy, blind deconvolution were applied silica microbeads red blood cells images. MCR analysis produces restored that show informative structures are not noticeable initial images, demonstrates its capability multiplane amplitude objects. In comparison with methods set No Reference Images Quality Metrics (NR-IQMs) Standard Deviation, ENTROPY Average Gradient, Auto Correlation, our presents better values metrics, showing it can be used as alternative methods.