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This paper introduces a plug-and-play algorithm for enhancing compressive spectral imaging (CSI) through the integration of both a quadratic envelope (QE) regularizer and a deep prior. Our method employs the QE-based regularizer to foster a low-rank structure in conjunction with deep priors, synergistically integrated within a Plug-and-Play (PnP) framework. The distinct advantage of our chosen QE-regularizer is its propensity for uncovering low-rank solutions devoid of bias, distinguishing it from the nuclear norm. Through this fusion of QE and deep priors, we harness the complementary strengths of both techniques, resulting in a mutually reinforcing effect for CSI.
Bacca et al. (Mon,) studied this question.