Color eye ground image enhancement method based on imaging model

Abstract

The invention discloses a color eye ground image enhancement method based on an imaging model. The method can improve brightness and low contrast at the same time, and realize image data fidelity, and can effectively enhance the region of interest of clinical diagnosis; and comprises the steps of preprocessing the brightness; extracting foreground pixels and background pixels in a color eye ground image: estimating imaging model parameter-background brightness and an imaging model parameter-transmission coefficient; and finally performing image enhancement according to the imaging model: substituting the background brightness and the transmission coefficient into the imaging model for calculation to obtain an enhanced image.

Description

technical field [0001] The invention belongs to the technical field of image enhancement, and in particular relates to an image enhancement method of a color fundus map based on an imaging model. Background technique [0002] The screening of fundus images is an effective means to collect retinal information of patients. Whether it is manual diagnosis or computer-aided automatic diagnosis, high-quality fundus images are very important for lesion detection and reliable diagnosis results. Due to eye diseases, imaging equipment, and patient cooperation, the obtained fundus images often have problems such as uneven brightness and low contrast. The low contrast in the fundus image will cause the characteristics of the fundus structure and lesion structure to be blurred, which will seriously affect the correct diagnosis of fundus diseases. Since the low contrast of fundus images is sometimes caused by ocular lesions, such as cataracts, image quality cannot be improved by reacquir...

AI Technical Summary

Problems solved by technology

At present, most of the enhancement techniques for color fundus images are only used to detect fundus structures and preprocessing of lesions, so they can only enhance some structures in the fundus images, but cannot enhance the overall fundus image

According to the needs of clinical diagnosis, it is hoped to enhance the fundus map as a whole. The existing fundus map enhancement methods only process different channels of the color fundus map separately. Due to the lack of prior information of the original image, it is difficult to achieve image visual effects. Fidelity, and not ideal for enhancing blurry images

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