Hyperspectral Image Reconstruction for Interferometric Spectral Imaging System with Degradation Synthesis  

作　　者：Yuansheng Li Xiangpeng Feng Siyuan Li Geng Zhang Ying Fu 

机构地区：[1]School of Computer Science and Technology,Beijing Institute of Technology,Beijing 100081,China [2]Xi’an Institute of Optics and Precision Mechanics,CAS,Xi’an 710119,China

出　　处：《Journal of Beijing Institute of Technology》2025年第1期42-56,共15页北京理工大学学报(英文版)

摘　　要：Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferometric imaging faces the impact of multi-stage degradation. Most exsiting interferometric spectrum reconstruction methods are based on tradition model-based framework with multiple steps, showing poor efficiency and restricted performance. Thus, we propose an interferometric spectrum reconstruction method based on degradation synthesis and deep learning.Firstly, based on imaging mechanism, we proposed an mathematical model of interferometric imaging to analyse the degradation components as noises and trends during imaging. The model consists of three stages, namely instrument degradation, sensing degradation, and signal-independent degradation process. Then, we designed calibration-based method to estimate parameters in the model, of which the results are used for synthesizing realistic dataset for learning-based algorithms.In addition, we proposed a dual-stage interferogram spectrum reconstruction framework, which supports pre-training and integration of denoising DNNs. Experiments exhibits the reliability of our degradation model and synthesized data, and the effectiveness of the proposed reconstruction method.

关 键 词：hyperspectral imaging degradation modeling data synthesis spectral reconstruction 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]