This paper addresses the difficulty of generating High Dynamic Range (HDR) images using current Low Dynamic Range (LDR) camera technology. Typically, several LDR images must be acquired using various camera f-stops and then the images must be blended using one of several exposure bracketing techniques to generate HDR images. Based on Fourier analysis of typical Color Filter Array (CFA) sampled images, we demonstrate that the the existing CFA sampled images provide information that is currently underutilized. This thesis presents an approach to generating HDR images that uses only one input image while exploiting that underutilized CFA data. We propose that information stored in unsaturated color channels is used it to enhance or estimate details lost in saturated regions. A demonstration of experimental data is presented for an optimized combination of demosaicing, color balance, gamma correction, and HDR image generation.
As an extension of the HDR imaging and CFA research presented herein, multispectral imaging is also explored. We develop a theory for acquiring multispectral image data based on the Fourier analysis of the relationships in the spatial-spectral signals which then leads to the design of a multispectral CFA.