Retinal image semi-blind deconvolution restoration based on dual tree complex transform

A combination of dual tree complex transform and the image processing algorithm of semi-blind deconvolution was proposed to eliminate the factors which make the image worse. Firstly, the retinal image obtained from the adaptive optics system was decomposed with dual tree complex transform into two parts. The low frequency image was processed by the algorithm of semi-blind deconvolution with some constraints. And the optical transfer function was used as initial parameter estimate which was constructed with the residual aberration of image system. The high frequency image was processed by denoising. Finally, the goal image was obtained by combining the processed images. The experimental results show that the retinal image quality is improved with this method, the image objective quality evaluation parameters are increased more than 5 times compared with the original image, and the average power spectrum is improved about 6 times in the spatial frequency range(70~90()-1) of retinal cells, which show that the method can contribute to satisfying the requirement of observation of human retinal image.