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With the advent of the big data era, extracting meaningful structures and patterns from massive, high-dimensional, and redundant data has become a critical challenge in machine learning and signal processing. Sparse coding (SC) is an effective unsupervised learning method that reveals the intrinsic structure and latent regularities of data by s ...

Table of Contents Article Overview Framework Workflow Code Analysis Article Overview Problem Context: Hyperspectral compressive imaging utilizes compressed sensing theory to capture hyperspectral data through snapshot measurements via coded apertures, avoiding temporal scanning. The core challenge lies in reconstructing the original hypers ...