Based on multiple fields of view (FOV) point spread function (PSF) estimation, we propose a novel gradient-constrained image restoration method to solve optical degradation in microscopic imaging. The whole FOV is segmented into several parts. The modulation transfer function (MTF) is measured to obtain the corresponding PSF for each part. L0 gradient constraint is treated as a regularization term, a fast image restoration method is designed to deblur degraded images of each field of view. Finally, gradual weight approach is used to stitch the multiple field of view (m-FOV) restoration images. Several microscopic images are tested and evaluated. Comparing with other methods, the results indicate that our method performs better, and runs fastest of all.
In this paper, a motion deblurring method with long/short exposure image pairs is presented. The long/short exposure image pairs are captured for the same scene under different exposure time. The image pairs are treated as the input of the deblurring method and more information could be used to obtain a deblurring result with high image quality. Firstly, the luminance equalization process is carried out to the short exposure image. And the blur kernel is estimated with the image pair under the maximum a posteriori (MAP) framework using conjugate gradient algorithm. Then a L0 image smoothing based denoising method is applied to the luminance equalized image. And the final deblurring result is obtained with the gain controlled residual image deconvolution process with the edge map as the gain map. Furthermore, a real experimental optical system is built to capture the image pair in order to demonstrate the effectiveness of the proposed deblurring framework. The long/short image pairs are obtained under different exposure time and camera gain control. Experimental results show that the proposed method could provide a superior deblurring result in both subjective and objective assessment compared with other deblurring approaches.
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