Microscopic imaging quality improvement through L0 gradient constraint model based on multi-fields of view analysis

Abstract

The degradation of optical microscopic imaging is space-variant, and how to fast restore optical degraded image remains a special problem. Based on point spread function (PSF) estimation under each field of view (FOV), a L0 gradient-constrained image restoration method is proposed to solve optical degradation in microscopic imaging. Firstly, the whole scene is segmented into several different regions according to different FOV. The PSFs for each region are estimated from modulation transfer function (MTF) measured in advance. Secondly, a penalty function is designed using L0 gradient constraint to deblur the degraded images of each sub-FOV. Finally, a weighted stitching approach is used to stitch the restored images of multiple FOV (m-FOV). Experimental results indicate that the m-FOV analysis could well solve the problem of space-variant degradation. Compared with the other methods, both subjective and objective evaluation results prove that the L0 norm idea could rapidly and effectively restore the degraded image. The approach could be well applied to a real product.