关键词:
Image reconstruction
摘要:
Interferometric spectral imagers enable simultaneous acquisition of two-dimensional spatial information and one-dimensional spectral data of targets. It offers significant advantages, including high throughput, multi-channel capability and superior resolution, with broad applications in agricultural vegetation analysis, soil composition assessment, marine biology studies, atmospheric monitoring and mineralogical investigations. The workflow involves dispersion, interference and imaging to capture target's images and interference information, from which spectral information is reconstructed. However, during the acquisition of interferograms, deviations arise due to factors such as the nonuniform response of the detector itself, variations in signal processing circuits across different sub-regions, environmental fluctuations affecting the detector's operation, and non-uniformity in optical energy transmission. These deviations prevent the interferograms from accurately representing the target's spatial and spectral characteristics, resulting in spectral distortion during reconstruction. Consequently, prior to spectral reconstruction, interferogram correction must be performed through steps including dark current correction, response non-uniformity compensation, and bad pixel correction to mitigate the impact of various errors on the reconstructed spectrum. The corrected interferogram represents a superposition of high-frequency information and low-frequency background noise that varies with optical path difference. The low-frequency component adversely affects the accuracy of spectral reconstruction and should be eliminated through filtering. Current interferogram filtering methodologies primarily encompass differential method, fitting method, and empirical mode decomposition (EMD). While differential method inherently compromises interference curve symmetry, fitting-based method demands prior knowledge of signal characteristics and empirical mode decomposition has dr