顾及影像稀疏特性的压缩感知超分辨率重建  

Reconstruction of compressed sensing super-resolution with consideration of image sparse feature

作　　者：李春梅 邓喀中[1] 孙久运 王慧[1] LI Chunmei;DENG Kazhong;SUN Jiuyun;WANG Hui(School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China;School of Geography,Geomatics and Planning,Jiangsu Normal University,Xuzhou,Jiangsu 221116,China)

机构地区：[1]中国矿业大学环境与测绘学院,江苏徐州221116 [2]江苏师范大学地理测绘与城乡规划学院,江苏徐州221116

出　　处：《测绘科学》2018年第10期82-89,共8页Science of Surveying and Mapping

基　　金：国家自然科学青年基金项目(41701380)

摘　　要：针对传统压缩感知信号重构仅实现对原始图像的复原和逼近,无法实质性提高影像分辨率问题,该文提出一种非退化的压缩感知超分重构方法:从图像传感器的结构分析数字影像的稀疏特性,进而以插值图像为指导,采用非线性的压缩感知优化重建方法,实现了非退化的单帧图像超分辨率重建。研究表明:该文方法改变了影像采集的过程和途径,弥补了传统压缩感知信号重构无法实质性提高影像分辨率的缺陷,且其重建图像的视觉效果及定量指标均优于传统插值法。Aiming at the problem that traditional compressed sensing signal reconstruction can only restore or approximate the original image without improving the image resolution,a method was proposed to reconstruct the non-degenerate compressed sensing super-resolution in this study.This study began with analysis of the sparse characteristics of digital image from the image sensor structure to achieve non-degenerate single-frame-image reconstruction,guided by interpolation images and using nonlinear compressive sensing reconstruction algorithm.This research indicated that the proposed method changed the image acquisition process and channel,remedied the defect of traditional compressed sensing which cannot substantially improve the image resolution,and increased visual effects and quantitative indicators effectively,which were better than those of traditional interpolation methods.

关 键 词：图像传感器 摄影测量 压缩感知 稀疏表示 信号重构 超分辨率重建 

分 类 号：P231[天文地球—摄影测量与遥感]