As regards L p norms with p < 2, we start by defining these norms. For a matrix A, ||A||p=∑i,j|aij|pp where a ij are the elements of A. The defining feature of these prior models is that they are concentrated on images with low average amplitude with few outliers standing out. Thus, they are suitable when the prior information is that the image contains small and well localized objects as, for example, in the localization of cortical activity by electric measurements.
