西安电子科技大学学报（自然科学版）2025，Vol.52Issue(2)：143-155,13.DOI:10.19665/j.issn1001-2400.20241103
梯度递归模型优化注入系数的全色锐化算法
Gradient recursive optimization based injection coefficient algorithm for pansharpening
摘要
Abstract
Pansharpening is to fuse the panchromatic(PAN)and multispectral(MS)images to produce High-Resolution Multispectral(HRMS)images,which is helpful for applications in ground object identification and land monitoring in the field of remote sensing.However,existing pansharpening methods based on multi-resolution analysis often overlook the relationship between the image gradients,leading to inaccuracies in extracting the detailed features from the source image and causing spatial distortion in the fusion results.To address these issues,this paper proposes a novel pansharpening method based on gradient recursion to optimize the injection coefficient.This method first analyzes the gradient relationship between the source and the fusion image.It constructs a recursive model between the ideal HRMS image and the source images at full-scale.Then,a gradient regression algorithm is designed to solve the injection coefficients iteratively.Finally,the injection coefficients are employed to refine the details obtained through a multi-resolution analysis,and the optimized details are injected into the MS image to generate the optimal HRMS image.The method is tested through simulation and real experiments on three datasets,including Pléiades,IKONOS,and WorldView-3.Compared to the second-best performing method,the ERGAS values increase by 3.59％,4.46％,and 2.18％in the simulation experimental results,respectively,and the QNR values also increase by 3.83％and 1.92％in real experiments on the Pléiades and IKONOS datasets.However,the QNR value achieves a second-best performance on the WorldView-3 dataset.In ablation experiments,compared to a gradient-free pansharpening method,the ERGAS values increase by 11.33％,14.08％,and 1.95％respectively.The HRMS images generated by our method effectively integrate the spectral information from MS images with the spatial information from PAN images,thereby significantly enhancing HRMS's spectral and spatial resolution,with the computational efficiency relatively fast.关键词
遥感/图像融合/全色锐化/注入系数/梯度/递归/迭代优化Key words
remote sensing/image fusion/pansharpening/injection coefficient/gradient/recursion/iterative optimization分类
信息技术与安全科学引用本文复制引用
戴欢,杨勇,卢航远,黄淑英,陈常杰..梯度递归模型优化注入系数的全色锐化算法[J].西安电子科技大学学报（自然科学版）,2025,52(2):143-155,13.基金项目
国家自然科学基金(62072218,62261025,62362035) （62072218,62261025,62362035）
天津市自然科学基金项目(24JCDJC00130) （24JCDJC00130）
江西省自然科学基金管理科学项目(20213BAA10W03) （20213BAA10W03）
江西省重点研发计划重点项目(20243BBG71032,20243BBG71036) （20243BBG71032,20243BBG71036）
