We introduce a technique to automatically correct color inconsistencies in a display composed of one or more digital light projectors (DLP). The method is agnostic to the source of error and can detect and address color problems from a number of sources. Examples include inter- and intra-projector color differences, display surface markings, and environmental lighting differences on the display. In contrast to methods that discover and map all colors into the greatest common color space, we minimize local color discontinuities to create color seamlessness while remaining tolerant to significant color error. The technique makes use of a commodity camera and highdynamic range sensing to measure color gamuts at many different spatial locations. A differentiable energy function is defined that combines both a smoothness and data term. This energy function is globally minimized through the successive application of projective warps defined using gradient descent. After convergence the warps can be applied at runtime to minimize color defects in the display. The framework is demonstrated on displays that suffer from several sources of color error.

This thesis deals with color correction of a chain that starts with the 3D Artec MHT scanner, and ends with the 3D printers (CJP – Color Jet Printing technology). In principle, it is necessary to control the color interpretation of the entire chain from the scanning of real models to the 3D print model. With color properties and their color shade, including color textures. The principle of model surface scanning using a 3D scanner is in the same principle as photo camera which scans using a conventional CMOS chip. For this reason, color palettes were scanned using the photo camera and the resulting digital data were analyzed by the Darktable software. This analysis consisted of comparing the scanned color shades of the surface with the spectrofotometer measured data. The main goal of this method was to achieve color precision in the digital data during their acquirement, adjustment and interpretation. Then the same principle was applied to the data acquired by the 3D scanner to create an ICC profile of the 3D scanner. Because the 3D printer (CJP – Color Jet Printing) uses the same principle as the 2D printer, the 2D printing device calibration principle was used again to calibrate it. There have been defined procedures that adjust the color shade to the spectrophotometrically correct shades of the resulting print on a 3D printer. Color swatches were also printed for print quality verification. It has been found that with photo camera, which was used for objective measurement in the L*a*b* coordinates of independent space, any color setting and their adjustment is very sensitive to even small imprecisions. It has been found that it is not easy to obtain accurate colors within the Detla E

Mini Unmanned Aerial Vehicles (mUAVs) have the potential to be a great asset to Wilderness Search and Rescue groups by providing a bird's eye view of the search area. These vehicles can carry a variety of sensors to better understand the world below. This paper proposes using both Infrared (IR) and Visible Spectrum cameras on a mUAV for Wilderness Search and Rescue. It details a method for combining the color and heat information from these two cameras into a single fused display to reduce needed screen space for remote field use. To align the video frames for fusion, a method for simultaneously pre-calibrating the intrinsic and extrinsic parameters of the cameras and their mount using a single multi-spectral calibration rig is also presented. A user study conducted to validate the proposed image fusion methods showed no reduction in performance when detecting objects of interest in the single-screen fused display compared to a side-by-side display. Furthermore, the users' increased performance on a simultaneous auditory task showed that increased performance on a simultaneous auditory task showed that their cognitive load was reduced when using the fused display.