计算技术与自动化2024，Vol.43Issue(4)：97-103,7.DOI:10.16339/j.cnki.jsjsyzdh.202404016
基于像素紧密程度的多源遥感影像信息提取方法
A Method for Extracting Information from Multisource Remote Sensing Images Based on Pixel Tightness
摘要
Abstract
During the collection process of remote sensing images,there are a large number of ground cover types with low clarity and resolution.The threshold measurement standards between key pixel features are blurry,which increases the difficulty of information extraction and reduces information utilization.Therefore,a multi-source remote sensing image in-formation extraction method based on pixel compactness is proposed.Utilizing Contourlet transformation to achieve multi angle enhancement in the spatial and transformation domains of remote sensing images,optimizing the overall clarity of re-mote sensing images.Using the SLIC superpixel algorithm to calculate the closeness between pixel clustering centers and neighboring pixels,eliminating the influence of fixed thresholds.Introducing GLCM gray level co-occurrence matrix to ex-tract subject feature information.The classification model of relevance vector machine is constructed,and the extraction problem is transformed into noise regression problem by combining with the Laplace quadratic approximation regression al-gorithm,and the solution is expanded to realize the information extraction of remote sensing images.The experimental re-sults show that the classification of remote sensing information subjects using the proposed method is basically consistent with the classification of real remote sensing information subjects.The error extraction rate and omission extraction rate are low during the information extraction process,and the overall extraction accuracy remains above 99％.Moreover,the clarity of road information extraction is high,indicating that the method improves the interpretation level of remote sensing infor-mation.关键词
Contourlet变换/SLIC超像素分割法/CIE LAB色彩空间/GLCM灰度共生矩阵/相关向量机分类模型Key words
Contourlet transformation/SLIC super pixel segmentation method/CIE LAB color space/GLCM gray-level co-occurrence matrix/correlation vector machine classification model分类
信息技术与安全科学引用本文复制引用
洪倩,李志斌,陈晓枫,李本良,臧玉魏..基于像素紧密程度的多源遥感影像信息提取方法[J].计算技术与自动化,2024,43(4):97-103,7.基金项目
国网总部管理科技项目(5500-202056438A-0-0-00) （5500-202056438A-0-0-00）
