Image simulation of HSI systems

Bradley D. Paul; Adam J. Rossi

doi:10.1117/12.2632363

30 September 2022 Image simulation of HSI systems

Bradley D. Paul, Adam J. Rossi

Proceedings Volume 12235, Imaging Spectrometry XXV: Applications, Sensors, and Processing; 122350G (2022) https://doi.org/10.1117/12.2632363
Event: SPIE Optical Engineering + Applications, 2022, San Diego, California, United States

Abstract

Modeling and simulation of imaging systems is a critical capability used throughout the lifetime of a remote sensing system. Simulating HSI systems is challenging because the mathematical methods and models used for a normal PAN or MSI system with filters cannot be used, as the vast shape diversity of the Point Spread Function (PSF) across the image plane prevents the use of an Optical Transfer Function (OTF). Provided that the HSI system satisfies the condition t_int∆f ≫ 1, where t_int is the integration time and ∆f is the channel bandwidth, one can avoid the complexities of partial coherence and add intensities at the focal plane. For every sub-sampled wavelength and sub-sampled location in the image plane, a unique superposition PSF needs to be computed. This requires optimized GPU CUDA kernels running in a high performance computing environment controlled with Message Passing Interface (MPI). The simulation is broken into five key steps: (1) creation of EAR hyper-cubes for each step of the CONOPS using RIT's Digital Imaging and Remote Sensing Image Generation (DIRSIG), (2) GPU accelerated Fourier Optics propagation to create superposition kernels derived from local PSFs, (3) application of the kernels to the processed DIRSIG hyper-cubes using superposition integration, (4) simulation of Focal Plane Array (FPA) detector properties, and (5) assembling the final hyper-cube image and metadata from the sequence of FPA data sets.

Conference Presentation

Citation Download Citation

Bradley D. Paul and Adam J. Rossi "Image simulation of HSI systems", Proc. SPIE 12235, Imaging Spectrometry XXV: Applications, Sensors, and Processing, 122350G (30 September 2022); https://doi.org/10.1117/12.2632363

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