Discrete camera calibration from the information distance between pixel streams

We consider the problem of estimating the relative orientation of a number of individual photocells -or pixels- that hold fixed relative positions. The photocells measure the intensify of light traveling on a pencil of lines. We assume that the light-field thus sampled is changing, e.g. as the result of motion of the sensors and use the obtained measurements to estimate the orientations of the photocells. We explore an information-theoretic and geometric approach: based on real-world data, we build a non-parametric functional relation linking the information distance between the data streams of two photocells, and the angular separation between the photocells. Then, given data streams produced by arrays of pixels in similar conditions, we use the functional relation to estimate the angles between pixels. Finally, we embed the estimated angles in the unit 3D sphere to obtain the estimated layout of the array.