PROJECT TITLE :
Parameter-Free Gaussian PSF Model for Extended Depth of Field in Brightfield Microscopy
ABSTRACT:
Conventional brightfield microscopes have a restricted depth of field, which prevents them from fully focusing on thick specimens. All-in-focus images can be obtained by optically sectioning the specimen and then using the multi-focus fusion method to acquire z-stacks of images. For undersampled picture stacks, fusion algorithms are unable to remove the blur in areas where the in-focus position is between two optical sections. This is a limitation. All in focus images, depth maps, and sample distances in the picture plane may be approximated from a sequence of images using a parameter-free Gaussian PSF model, which does not require knowledge of the z-stack acquisition process. Maximal A posteriori framework, an adaptive scaled gradient descent approach is used to estimate the depth map and sample distances efficiently by repeatedly reweighting the least squares method. Experimental results show that the suggested method is superior than current methods, reducing artefacts and regaining crisper edges from data sets that are both synthetic and genuine.
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