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Estimation of Point Spread Function (PSF) in Hyperspectral Images

Pirhosseinlou, Ali | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58486 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Amini, Arash
  7. Abstract:
  8. Hyperspectral images are utilized in various fields due to their rich spectral information, but they often suffer from blur induced by the optical system, which is typically variable across the spectrum. Accurate estimation of this blur is essential for correct information retrieval. This research presents a novel optimization framework for the accurate and efficient estimation of Point Spread Function (PSF) in hyperspectral images. The core innovation of this method is the introduction of a "spectral coupling" constraint, which models the smooth variations of the PSF among adjacent bands, significantly enhancing the stability of the estimation. By transforming the problem into the Fourier domain, a closed-form, non-iterative solution is derived, wherein the problem is decoupled into numerous small, independent systems of linear equations—one for each frequency component. This characteristic leads to a very fast and fully parallelizable algorithm, ideal for implementation on Graphics Processing Units (GPUs). Evaluations performed on controlled synthetic data demonstrate the high accuracy of the proposed method in terms of PSNR. This framework provides a fast, accurate, and robust solution for the variable deblurring problem in hyperspectral images
  9. Keywords:
  10. Hyperspectral Imaging ; Image De-Blurring ; Point Spread Function ; Analytical Closed Form Solution ; Spectrally-Varying Blur ; Spectral Coupling