3D Image Deblur Using Point Spread Function Modelling for Optical Projection Tomography

Optical projection tomography (OPT) is widely used to produce 3D image for specimens of size between 1mm and 10mm. However, to image large specimens a large depth of field is needed, which normally results in blur in imaging process, i.e. compromises the image quality or resolution. Yet, it is important to obtain the best possible quality of 3D image from OPT, thus deblurring the image is of significance. In this paper we first model the point spread function along optical axis which varies at different depths in OPT imaging system. The magnification is taken into account in the point spread function modelling. Afterward, deconvolution in the coronal plane based on the modelled point spread function is implemented for the image deblur. Experiments with the proposed approach based on 25 3D images including 4 categories of samples, indicate the effectiveness of quality improvement assessed by image blur measures in both spatial and frequency domain.