Gaussian Surrogates for Poisson Imaging: Some Theoretical and Empirical Results
The study compares Gaussian surrogate objectives against Poisson-based methods for imaging problems where measurements follow a Poisson distribution, especially in low-dose scenarios. The research found that proper regularization can make simple quadratic objectives competitive with traditional Poisson estimators by mitigating variance spikes inherent in low-count data.