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Efficient and Convergent Algorithms for High-Fidelity Hyperspectral Image Fusion
Hyperspectral (HS) imaging refers to acquiring images with hundreds of bands corresponding to different wavelengths of light. HS imaging has a wide range of applications such as remote sensing, industrial inspection, ...
Novel Regularized Image Reconstruction Algorithms for Sparse Photoacoustic Tomography
Among all tissue imaging modalities, photo-acoustic tomography (PAT), has been getting increasing attention in the recent past due to the fact that it has high contrast, high penetrability, and has capability of retrieving ...
Improved Derivative-based Regularizations for Imaging Inverse problems
Images undergo degradation during the capturing process due to physical
limitations inherent to the capturing devices. Addressing this degradation and
recovering high-quality images constitute the image recovery problem, ...