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In recent years, light field (LF) capture and processing has become anintegral part of media production. The richness of information available in LFshas enabled novel applications like post-capture depth-of-field editing, 3Dreconstruction, segmentation and matting, saliency detection, object detectionand recognition, and mixed reality. The efficacy of such applications dependson certain underlying requirements, which are often ignored. For example, someoperations such as noise-reduction, or hyperfan-filtering are only possible ifa scene point Lambertian radiator. Some other operations such as the removal ofobstacles or looking behind objects are only possible if there is at least oneray capturing the required scene point. Consequently, the ray distributionrepresenting a certain scene point is an important characteristic forevaluating processing possibilities. The primary idea in this paper is toestablish a relation between the capturing setup and the rays of the LF. Tothis end, we discretize the view frustum. Traditionally, a uniformdiscretization of the view frustum results in voxels that represents a singlesample on a regularly spaced, 3-D grid. Instead, we use frustum-shaped voxels(froxels), by using depth and capturing-setup dependent discretization of theview frustum. Based on such discretization, we count the number of rays mappingto the same pixel on the capturing device(s). By means of this count, wepropose histograms of ray-counts over the froxels (fristograms). Fristogramscan be used as a tool to analyze and reveal interesting aspects of theunderlying LF, like the number of rays originating from a scene point and thecolor distribution of these rays. As an example, we show its ability bysignificantly reducing the number of rays which enables noise reduction whilemaintaining the realistic rendering of non-Lambertian or partially occludedregions.

Fristograms: Revealing and Exploiting Light Field Internals