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Hyperparameter Analysis for Derivative Compressive Sampling

2021-08-05 20:58:18
Md Fazle Rabbi
arXiv_CV
     
Abstract

Derivative compressive sampling (DCS) is a signal reconstruction method from measurements of the spatial gradient with sub-Nyquist sampling rate. Applications of DCS include optical image reconstruction, photometric stereo, and shape-from-shading. In this work, we study the sensitivity of DCS with respect to algorithmic hyperparameters using a brute-force search algorithm. We perform experiments on a dataset of surface images and deduce guidelines for the user to setup values for the hyperparameters for improved signal recovery performance.

Abstract (translated)

URL

https://arxiv.org/abs/2108.04355

PDF

https://arxiv.org/pdf/2108.04355.pdf

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