Disregarding spectral overlap — A unified approach for demosaicking, compressive sensing and color filter array design

Abstract

Modern Color Filter Array (CFA) designs avoid overlap of luminance and chrominance spectra as it is widely believed to cause irreversible crosstalk and aliasing. In this paper, we present a simple formulation of the demosaicking problem that disregards spectral overlap -and thus the geometry of the spectra -and instead connects the luminance and chrominance resolutions in a more fundamental way to the photosite density of the sensor.A linear universal demosaicker consisting of space variant filters results from this formulation along with CFA designs that capture more image information than competing designs. This includes the interesting class of random RGB designs that outperform the Bayer CFA with nonlinear demosaickers in terms of PSNR and have a number of additional desirable properties.Furthermore, we present non-linear enhancements to our universal demosaicker and show them to be either related to compressive sensing or an alternate reconstruction algorithm for it.

Universal Demosaicking of Color Filter Arrays

“…Hore and Ziou in [14] added an edge-sensing mechanism to the universal method in [19] and unanimously improved the demosaicking performance with all the seven uniform CFAs they tested. Another universal demosaicking was proposed by Singh and Singh [48], which is non-iterative and using space-variant filters for random CFAs. The method is based on the generalized inverse of the matrix for CFA sampling relations of primary colors.…”

Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence

“…Although derived by the simulation with commercial absorption filters illustrated in Figure 1 a, the experimental framework of the MLI method enhanced by the work in this article can be applied to other aspects such as transmittance design for SFA multispectral system and direct optimization of physical variables for filter manufacturing techniques. The criteria for selecting filter sets can serve as an explanation of why a broadband multispectral camera with overlapping spectral sensitivities works well for the conventional SFA multispectral system [ 14 , 15 , 16 , 17 , 29 , 30 , 31 ], and thus it would be serve as a criterion for designing the spectral sensitivity of SFA sensors. As a practical approach, filters could also be designed using direct optimization of dye concentrations [ 32 ], consequently, the criterion could guarantee a desired optimal filter set manufacturable in reality.…”

“…It is worth noting that the results of the best filter sets are amazing due to the fact their shapes are somehow similar to those of the transmittances curve of the state-of-art SAF, however it does not mean that the MLI method advanced above can be directly applied to SAF design. It would be a good idea to use the scoring or ranking method described in the manuscript to search for the other types of optimal filter sets [ 14 , 15 , 16 , 17 , 29 , 30 , 31 ]. In a typical case, the authors try to find five optimal filters of Gaussian curve type by varying five parameters [ 31 ].…”