The presented analyses of the general model can be projected onto many practical applications, e.g., hyperspectral imaging, source localization and synchronization.
There are also many practical limitations for medical imaging that is modality-dependent.
In practical imaging systems, many factors conspire to increase the luminance of black, thereby lessening the contrast ratio and impairing picture quality.
Consider the (l_{q} (0< q<1)) regularization problem min_{xinmathbb{R}^{n}} frac{1}{2} Vert Ax-b Vert ^{2}+lambda Vert x Vert _{q}, (4) which has many practical applications in compressed sensing and imaging science (see e.g., [1]), where (Vert x Vert _{q}=(sum_{i=1}^{n} vert x_{i} vert ^{q})^{1/q}).
However, it is difficult for these methods to clearly image the shape and sharp boundary of geological structures, although such an imaging is required in many practical situations (Marcuello-Pascual et al. 1992; Smith et al. 1999; Zhdanov 2004, 2009, 2010).
In many practical applications, for example, DNA microarrays [12], face recognition [13], color imaging [14], image annotation [15], multi-response linear regression [16], etc., the non-zero entries of sparse signal can be aligned or classified into blocks, which means that they appear in regions in a regular order instead of arbitrarily spread throughout the vector.
In many practical problems, such as geological exploration, forging technology and medical imaging, among others, it has been detected that the scattered data are usually arranged in parallel lines.
As with many biophotonics technologies, translating polarization imaging systems from the lab to the clinic raises many practical issues, partly because many current systems use a transmission geometry where the sample is located directly between the illumination source and the camera.
Optical attenuation from absorption and scattering in tissue typically limit how much light is recovered from depths beyond a few millimeters, and thus for many applications this inherent reduced depth range is not the limiting factor in determining the practical imaging depth.
But that leaves many practical questions unanswered.
