Fig. 1
From: Robust surface normal estimation via greedy sparse regression
Stylized visualization of three examples of linear equation systems. A and y represent the design matrix and observations, respectively; x is the unknown signal to be recovered. Positive and negative values are shown as coloured blocks, and zero entries are represented by black blocks. a Overdetermined system, where there are more observations (5) than unknowns (3). b Underdetermined system, where there are more unknowns (5) than observations (3). The signal x cannot be uniquely determined from such a system. c Underdetermined system with sparse signal. It is possible to recover x using sparse recovery methods as long as we know that x is sparse, even though the system is underdetermined and the exact positions of non-zero entries are not known a priori