Correlation-based color mosaic interpolation using a connectionist approach
Gary L. Embler · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
This paper presents a specialized extension of a general correlation-based interpolation paradigm, for interpolating image sample color values obtained through a color filter mosaic. This extension features a kernel determined from a priori assumed image characteristics in the form of pre- defined (as opposed to learned) local sample neighborhood patterns. The interpolation procedure locally convolves the color-filtered image samples with the kernel to obtain the interpolated color values. The kernel establishes a mapping from the color-filtered input values to the recovered color output values using weighted, ordered, and thresholded sums of sample values from the local sample neighborhood. This mapping attempts to exploit local image sample interdependencies in order to preserve detail, while minimizing artifacts. The procedure is simulated for the Bayer RGB color filter mosaic using a quasi-linear connectionist architecture that is real-time-hardware- implementable. A perceptual comparison of images obtained from this interpolation with images obtained from bilinear interpolation shows a visible reduction in interpolation artifacts.