DiriNet:An Estimation Network for Spectral Response Function and Point Spread Function  

作　　者：Ting Hu Siyuan Cheng Chang Liu 

机构地区：[1]Beijing Key Laboratory of Computational Intelligence and Intelligent System,Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China [2]Space Star Technology Co.,Ltd,Beijing 100086,China [3]Research Institute of Intelligent Wire-less Communication Network Technology,Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China

出　　处：《Journal of Beijing Institute of Technology》2024年第4期287-297,共11页北京理工大学学报（英文版）

基　　金：the Postdoctoral ScienceFoundation of China(No.2023M730156);the NationalNatural Foundation of China(No.62301012).

摘　　要：Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.

关 键 词：Dirichlet network point spread function spectral response function hyper-spectralimage multi-spectral image 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]