Blind Deterministic Compressive Sensing for Biomedical Images

Abstract

Compressive sensing (CS) enables us to reconstruct a signal from a few number of measurements obtained from a random or deterministic measurement matrix. Knowledge of the sparsifying basis of the signal is required for the recovery process. In this work, we use a recently developed deterministic measurement matrix and demonstrate recovery of the original signal from compressed samples without the knowledge of the sparsifying basis or the order of sparsity. We experimented this recovery on the Biomedical images. Using smoothed ℓ0-norm (SL0) as a recovery algorithm, the original images were recovered from CS measurements with high quality.