A method and system for removing image highlights affected by object surface highlight reflections

Abstract

The invention provides a method and system for removing image highlights affected by object surface highlight reflections. The method includes: S1, based on the SVM model, separating the highlight pixels of the image; S2, using the adjacent regions of the image with structural similarity to assign values ​​to the highlight pixel area. The present invention utilizes the method of statistical learning, and based on the SVM classifier, realizes the automatic separation of the high-light pixels of the endoscopic image. This method makes full use of the advantages of sample learning. After the separation model is obtained through training, the optimal separation model can be made without manual participation. Classification results; In terms of image restoration, in order to make full use of the effective information of the neighborhood with structural similarity in the whole image, the present invention proposes an image restoration method based on dynamic search and similarity measurement to realize natural restoration of highlight regions.

Description

technical field [0001] The present invention relates to the field of image processing, and more specifically, to a method and system for removing high light from an image affected by high light reflection on the surface of an object. Background technique [0002] At present, compared with traditional surgery, minimally invasive surgery only causes very small trauma to human tissue, and this technology can significantly reduce postoperative recovery time and mortality. Therefore, research on minimally invasive surgery and related auxiliary diagnosis and treatment methods has become a hot spot in medical technology research today. [0003] Endoscopic images provide clinicians with a true view of the internal environment as well as organ surfaces. An endoscope usually refers to a fixed tubular camera with a fiber optic light source fixed at the top of the camera for illumination and imaging. During the operation, the surgeon can obtain a real-time image of the surgical scene ...

AI Technical Summary

Problems solved by technology

[0006] Although the above method can obtain the basic separation and visual repair effect of the highlight area, the robustness and accuracy of highlight separation and the visual effect of highlight removal need to be improved and improved.

Moreover, threshold-based methods are often difficult to determine the optimal threshold, and analysis-based algorithms require manual intervention, which restricts the applicability of the algorithm.

Methods based on interpolation or using neighboring pixels at a single distance to repair the highlight area often fail when the highlight area is large

Images