AH-HIS: An adaptive pseudo-color enhancement method for high grayscale X-ray film weld images

AH-HIS: An adaptive pseudo-color enhancement method for high grayscale X-ray film weld images | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article AH-HIS: An adaptive pseudo-color enhancement method for high grayscale X-ray film weld images Mengyu Sun, Xiaoyan Li, Bingwu Liu, Peng Wang, Ruohai Di, Liangliang Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6806276/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aiming at the problems of poor adaptability and insufficient robustness of existing high-grayscale image pseudo-color enhancement methods. An adaptive pseudo-color enhancement algorithm for high-grayscale X-ray film weld seam images based on Hue, Saturation and Brightness color space is proposed. Firstly, a pixel self-transformation is performed on the original high-grayscale X-ray weld image. And assign the converted B, G and R values to the H, I, and S components in the HIS color space respectively. Secondly, because of the poor universality of the algorithm and the difficult dynamic adjustment of the HIS color space. The power adjustment and the grayscale correction is integrated into the constructed high gray scale HIS pixel self-transformation function, and an adaptive gray scale correction algorithm based on BP neural network is proposed and designed. Finally, the HIS component is converted to the RGB color space for display. The experimental results show that the pseudo-color enhancement method proposed in this paper can effectively improve the recognition of image defects. In the processing of low-contrast images, compared with the HIS algorithm used for low-grayscale weld ray images, all indicators have a better result. Among them, the entropy increased by 1.216%, contrast increased by nearly 2 times, image clarity index IL-NIQE increased by nearly 39.171%, and NIQE increased by 8.79%. Physical sciences/Mathematics and computing/Computer science Physical sciences/Engineering/Mechanical engineering X-ray weld defects adaptive image enhancement HIS color space BP neural network Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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