An Improved Algorithm of Removing Adherent Noise Based on Binocular Vision

doi:10.3969/j.issn.1006-2475.2023.06.011

Abstract

Abstract: In order to remove the image noise caused by the attachments on the lens or protective glass, a fast denoising algorithm based on binocular vision is proposed. Firstly, by introducing the step-by-step matching and integral map, the fast calculation of the real disparity map is realized. Secondly, the theoretical disparity of the attached noise is calculated by using the distance between the binocular camera and the glass where the attachment is located, and the noise localization is completed in combination with the actual disparity map. Then, image inpainting is used to estimate the disparities of the noise area, and the disparities of the pixels occluded by the attached noise is obtained. Finally, for the noise pixels in the left image, the estimated disparity is used to find the corresponding clean pixels in the right image and replace them to complete the removal of attached noise. The experiment compares the algorithm with the existing binocular vision-based denoising algorithm, and the results show that the algorithm can significantly improve the denoising speed while ensuring similar denoising effect. Compared with the learning-based denoising algorithm, this method has the advantages of stable denoising effect and will not identify other areas as noise.

Key words: adherent noise, binocular vision, step by step matching, integral image

CLC Number:

TP391.4

PENG Ming-kang, FENG Cheng-de. An Improved Algorithm of Removing Adherent Noise Based on Binocular Vision[J]. Computer and Modernization, 2023, 0(06): 62-68.

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