{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:47:46Z","timestamp":1776811666157,"version":"3.51.2"},"reference-count":18,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2023,5,30]]},"abstract":"<jats:p>Aiming at the problems of high feature mismatch rate and low matching efficiency in the current virtual image multi feature matching algorithm, a virtual image multi feature matching algorithm based on 3D scene reconstruction is proposed. Firstly, in the 3D scene reconstruction, the virtual image is preprocessed to eliminate the noise in the virtual image, avoid the noise interference in the compression process, and improve the signal-to-noise ratio of the image; Secondly, the de-noising virtual image is enhanced to enhance the details of the image; Finally, the corresponding information feature vector is constructed from the information features extracted from the virtual image, and the virtual image multi feature matching algorithm is completed. Experiments show that the multi feature matching rate of the designed algorithm is high, the error matching rate is low, the maximum spatial distortion rate is only 0.6%, and the compressed image quality and matching performance are good.<\/jats:p>","DOI":"10.3233\/jcm-226757","type":"journal-article","created":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T12:15:14Z","timestamp":1682684114000},"page":"1151-1163","source":"Crossref","is-referenced-by-count":0,"title":["Virtual image multi feature matching algorithm based on 3D scene reconstruction"],"prefix":"10.66113","volume":"23","author":[{"given":"Jun","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zongren","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaobo","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"1","key":"10.3233\/JCM-226757_ref1","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/s00530-019-00622-y","article-title":"Three-dimensional laser image-filtering algorithm based on multi-source information fusion and adaptive offline fog computing","volume":"26","author":"Wei","year":"2019","journal-title":"Multimedia Systems."},{"issue":"3","key":"10.3233\/JCM-226757_ref2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00340-021-07585-x","article-title":"A novel grayscale image encryption approach based on chaotic maps and image blocks","volume":"127","author":"Girdhar","year":"2021","journal-title":"Applied Physics B."},{"key":"10.3233\/JCM-226757_ref3","doi-asserted-by":"crossref","unstructured":"Ling S, Li J, Che Z, et al. Quality assessment of free-viewpoint videos by quantifying the elastic changes of multi-scale motion trajectories. IEEE Transactions on Image Processing. 2020; 30: 517-531.","DOI":"10.1109\/TIP.2020.3037504"},{"key":"10.3233\/JCM-226757_ref4","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.aca.2020.01.019","article-title":"Hyperspectral near infrared image calibration and regression","volume":"1105","author":"M\u00e4kel\u00e4","year":"2020","journal-title":"Analytica Chimica Acta."},{"issue":"1","key":"10.3233\/JCM-226757_ref5","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1007\/s10773-019-04103-w","article-title":"Improved Quantum Image Median Filtering in the Spatial Domain","volume":"58","author":"Jiang","year":"2019","journal-title":"International Journal of Theoretical Physics."},{"key":"10.3233\/JCM-226757_ref6","doi-asserted-by":"crossref","unstructured":"Gao P, Zhao D, Chen X. Multi-dimensional data modelling of video image action recognition and motion capture in deep learning framework. IET Image Processing. 2020; 14(7): 1257-1264.","DOI":"10.1049\/iet-ipr.2019.0588"},{"issue":"2","key":"10.3233\/JCM-226757_ref7","doi-asserted-by":"crossref","first-page":"3133","DOI":"10.1109\/JSTARS.2021.3062573","article-title":"Multi-Scale Image Matching for Automated Calibration of UAV-based Frame and Line Camera Systems","volume":"14","author":"Hasheminasab","year":"2021","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing."},{"issue":"2","key":"10.3233\/JCM-226757_ref8","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1049\/iet-cvi.2018.5496","article-title":"Image fusion method based on simultaneous sparse representation with non-subsampled contourlet transform","volume":"13","author":"He","year":"2019","journal-title":"IET Computer Vision."},{"issue":"1","key":"10.3233\/JCM-226757_ref9","first-page":"s12652","article-title":"Video teaching of piano playing and singing based on computer artificial intelligence system and virtual image processing","author":"He","year":"2021","journal-title":"Journal of Ambient Intelligence and Humanized Computing."},{"key":"10.3233\/JCM-226757_ref10","doi-asserted-by":"crossref","unstructured":"Yin F, Lin Z, Kong Q, et al. FedLoc: Federated learning framework for data-driven cooperative localization and location data processing. IEEE Open Journal of Signal Processing. 2020; 1: 187-215.","DOI":"10.1109\/OJSP.2020.3036276"},{"issue":"5","key":"10.3233\/JCM-226757_ref11","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.enganabound.2021.02.008","article-title":"Modelling the stability of a soil-rock-mixture slope based on the digital image technology and strength reduction numerical manifold method","volume":"126","author":"Yang","year":"2021","journal-title":"Engineering Analysis with Boundary Elements."},{"key":"10.3233\/JCM-226757_ref12","doi-asserted-by":"crossref","unstructured":"Jia XY, DongYe CL. Seismic section image detail enhancement method based on bilateral texture filtering and adaptive enhancement of texture details. Nonlinear Processes in Geophysics. 2020; 27(2): 253-260.","DOI":"10.5194\/npg-27-253-2020"},{"issue":"15","key":"10.3233\/JCM-226757_ref13","doi-asserted-by":"crossref","first-page":"4025","DOI":"10.1364\/AO.58.004025","article-title":"Multiple target information fusion matching algorithm based on a line laser and a single plane array camera.","volume":"58","author":"Li","year":"2019","journal-title":"Applied Optics."},{"issue":"6","key":"10.3233\/JCM-226757_ref14","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1109\/JSAC.2019.2904330","article-title":"Wireless traffic prediction with scalable Gaussian process: Framework, algorithms, and verification","volume":"37","author":"Xu","year":"2019","journal-title":"IEEE Journal on Selected Areas in Communications."},{"key":"10.3233\/JCM-226757_ref15","doi-asserted-by":"crossref","unstructured":"Teodoro AM, Bioucas-Dias JM, Figueiredo MAT. A Convergent Image Fusion Algorithm Using Scene-Adapted Gaussian-Mixture-Based Denoising. IEEE Transactions on Image Processing. 2019; 28(1): 451-463.","DOI":"10.1109\/TIP.2018.2869727"},{"issue":"11","key":"10.3233\/JCM-226757_ref16","first-page":"370","article-title":"Digital Image Progressive Fusion Simulation in Decoupling Cascaded Complex Networks","volume":"36","author":"He","year":"2019","journal-title":"Computer Simulation."},{"key":"10.3233\/JCM-226757_ref17","doi-asserted-by":"crossref","first-page":"102967","DOI":"10.1016\/j.infrared.2019.06.014","article-title":"A rapid detection method for dim moving target in hyperspectral image sequences","volume":"102","author":"Wang","year":"2019","journal-title":"Infrared Physics & Technology."},{"issue":"9","key":"10.3233\/JCM-226757_ref18","doi-asserted-by":"crossref","first-page":"1501","DOI":"10.3390\/rs12091501","article-title":"Remote sensing image semantic segmentation based on edge information guidance","volume":"12","author":"He","year":"2020","journal-title":"Remote Sensing."}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JCM-226757","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:06:51Z","timestamp":1776809211000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JCM-226757"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,30]]},"references-count":18,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/jcm-226757","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,30]]}}}