In clinical surgery, the quality of endoscopic images is degraded by noise. Blood, illumination changes, specular reflection, smoke, and other factors contribute to noise, which reduces the quality of an image in an occluded area, affects doctors’ judgment, prolongs the operation duration, and increases the operation risk. In this study, we proposed an improved weighted guided filtering algorithm to enhance endoscopic image tissue. An unsharp mask algorithm and an improved weighted guided filter were used to enhance vessel details and contours in endoscopic images. The scheme of the entire endoscopic image processing, which included detail enhancement, contrast enhancement, brightness enhancement, and highlight area removal, is presented. Compared with other algorithms, the proposed algorithm maintained edges and reduced halos efficiently, and its effectiveness was demonstrated using experiments. The peak signal-to-noise ratio and structural similarity of endoscopic images obtained using the proposed algorithm were the highest. The foreground–background detail variance–background variance improved. The proposed algorithm had a strong ability to suppress noise and could maintain the structure of original endoscopic images, which improved the details of tissue blood vessels. The findings of this study can provide guidelines for developing endoscopy devices.

In minimally invasive surgery, endoscopic image quality plays a crucial role in surgery. Aiming at the lack of a real parallax in binocular endoscopic images, this article proposes an unsupervised adaptive neural network. The network combines adaptive smoke removal, depth estimation of binocular endoscopic images, and the 3D display of high-quality endoscopic images. We simulated the smoke generated during surgery by artificially adding fog. The training images of U-Net fused by Laplacian pyramid are introduced to improve the network’s ability to extract intermediate features. We introduce Convolutional Block Attention Module to obtain the optimal parameters of each layer of the network. We utilized the disparity transformation relationship between left- and right-eye images to combine the left-eye images with disparity in HS-Resnet to obtain virtual right-eye images as labels for self-supervised training. This method extracts and fuses the parallax images at different scale levels of the decoder, making the generated parallax images more complete and smoother. A large number of experimental research results show that the scheme can remove the smoke generated during the operation, effectively reconstruct the 3D image of the tissue structure of the binocular endoscope, and at the same time, preserve the contour, edge, detail, and texture of the blood vessels in the medical image. Compared with the existing similar schemes, various indicators have been greatly improved. It has good clinical application prospects.

Background:In clinical surgery, the quality of endoscopic images is degraded by noise. Noise is mainly caused by blood, illumination changes, specular reflection, smoke, etc., which will significantly reduce the quality of the image in the occluded area. Affect the doctor's judgment, prolong the operation time and increase the operation risk.Methods:This paper proposes an improved weighted guided filtering algorithm to enhance endoscopic image tissue. An unsharp mask algorithm and an improved weighted guided filter are used to enhance vessel details and contours in endoscopic images. An overall scheme of endoscopic image processing is proposed, which includes detail enhancement, contrast enhancement, brightness enhancement and highlight area removal.Results:Compared with several other algorithms, it is better than other algorithms in maintaining edges and reducing halo, and its effectiveness is proved by experiments. The peak signal-to-noise ratio and structural similarity of endoscopic images obtained by the improved algorithm in this paper are the largest. The foreground-background value Detail Variance-Background Variance has been improved.Conclusion:Our algorithm has a stronger ability to suppress noise, and is more able to maintain the structure of the original endoscopic image, which improves the details of tissue blood vessels. This paper can provide guidelines for the development of endoscopy devices.

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