Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Evaluation and optimal design of spectral sensitivities for digital color imaging

The quality of an image captured by color imaging system primarily depends on three factors: sensor spectral sensitivity, illumination and scene. While illumination is very important to be known, the sensitivity characteristics is critical to the success of imaging applications, and is necessary to be optimally designed under practical constraints. The ultimate image quality is judged subjectively by human visual system. This dissertation addresses the evaluation and optimal design of spectral sensitivity functions for digital color imaging devices. Color imaging fundamentals and device characterization are discussed in the first place. For the evaluation of spectral sensitivity functions, this dissertation concentrates on the consideration of imaging noise characteristics. Both signal-independent and signal-dependent noises form an imaging noise model and noises will be propagated while signal is processed. A new colorimetric quality metric, unified measure of goodness (UMG), which addresses color accuracy and noise performance simultaneously, is introduced and compared with other available quality metrics. Through comparison, UMG is designated as a primary evaluation metric. On the optimal design of spectral sensitivity functions, three generic approaches, optimization through enumeration evaluation, optimization of parameterized functions, and optimization of additional channel, are analyzed in the case of the filter fabrication process is unknown. Otherwise a hierarchical design approach is introduced, which emphasizes the use of the primary metric but the initial optimization results are refined through the application of multiple secondary metrics. Finally the validity of UMG as a primary metric and the hierarchical approach are experimentally tested and verified

Filter Selection for Spectral Estimation Using a Trichrmatic Camera

Current imaging practices are based on exploiting metamerism to record and reproduce images. As a result, the data obtained in these images are dependent on the viewing conditions and the observer. While these methods produce acceptable results for day to day use, they often do not exhibit the type of accuracy and control required for scientific purposes such as art conservation. As a solution, many research institutions are now advocating the use of multispectral imaging to record the objects fundamental spectral properties to remove the data\u27s dependency on the observer and viewing environment. The research described in this thesis involved determining if a trichromatic camera and readily available filters can be used for spectral estimation purposes. The Pixel Physics TerraPix camera system was characterized, its response to a target and 105 Kodak Wratten Filters under tungsten illumination was simulated, and spectral reflectance estimations were generated. The top filter candidates were chosen based on their simulated performance. These filters were then used in an imaging experiment designed to approximate conditions that would be found in an art gallery or other place where copy work is performed. The results of the imaging experiment were compared with the simulation, and shortcomings of the model were identified. The results of the experiment show that a camera model can be used as a guiding tool to make filter selections for spectral estimation

Modifications of a sinarback 54 digital camera for spectral and high-accuracy colorimetric imaging: simulations and experiments

A search technique was used to identify sets of colored glass filters that could be placed in the optical path of the Sinarback 54 camera system resulting in improved color accuracy compared with a production unit and the ability to perform spectral estimation. A green and blue filter, each a pair of filters, were identified and constructed from Schott glass. RGB images were collected through these two filters resulting in six image planes. Using the Gretag Macbeth ColorChecker DC and a custom target of blue artist pigments, a transformation was derived that converted digitally flat-fielded and photometrically-linearized camera signals to estimated spectral reflectance factor. The combination of using these two filter “sandwiches” and appropriate mathematics resulted in more than a twofold improvement in color and spectral accuracy compared with the production camera. The average colorimetric and spectral performance is shown in the following bar graphs for the calibration targets and independent-verification targets, the Esser TE221 test chart, a custom target of artist pigments made using the Gamblin Conservation Colors, and the traditional GretagMacbeth ColorChecker Color Rendition chart. These results indicate that it is possible to achieve excellent color accuracy and acceptable spectral accuracy using a color-filter array sensor

Design and Construction of a Multispectral Camera for Spectral and Colorimetric Reproduction

Multi-spectral imaging and spectral reflectance reconstruction can be used in cultural-heritage institutes to digitalize their collections for documentation purposes. It can be used to simulate artwork under any lighting condition, and to analyze colorants that were used. The basic idea of a multi-spectral imaging system is to sub-sample spectral reflectance factor, producing results similar to a spectrophotometer. The sampled data are used to reconstruct reflectance for the visible spectrum. In this thesis, a wide band multispectral camera was designed and constructed to achieve high spectral and color accuracy as well as high image quality. Noise propagation theory was introduced and tested. A seven channel band- pass filter set was modeled using Gaussian functions and optimized to yield high spectral and colorimetric reproduction accuracy as well as low colori- metric noise. Single and sandwich filters were selected from o!-the-shelf absorption filters using the Gaussian bandpass filter model. Experiments were conducted to test the spectral, color and noise performance of the novel sandwich filters and compared with interference filters. The novel sandwich fil- ters led to increased colorimetric accuracy along with a reduction colorimetric noise. This imaging system will be used as part of a recommended workflow for museum archiving, and will be an important addition to the spectral imaging capabilities at MCSL

Combining transverse field detectors and color filter arrays to improve multispectral imaging systems

This work focuses on the improvement of a multispectral imaging sensor based on transverse field detectors (TFDs). We aimed to achieve a higher color and spectral accuracy in the estimation of spectral reflectances from sensor responses. Such an improvement was done by combining these recently developed silicon-based sensors with color filter arrays (CFAs). Consequently, we sacrificed the filter-less full spatial resolution property of TFDs to narrow down the spectrally broad sensitivities of these sensors.We designed and performed several experiments to test the influence of different design features on the estimation quality (type of sensor, tunability, interleaved polarization, use of CFAs, type of CFAs, number of shots), some of which are exclusive to TFDs.We compared systems that use a TFD with systems that use normal monochrome sensors, both combined with multispectral CFAs as well as common RGB filters present in commercial digital color cameras. Results showed that a system that combines TFDs and CFAs performs better than systems with the same type of multispectral CFA and other sensors, or even the same TFDs combined with different kinds of filters used in common imaging systems. We propose CFA+TFD-based systems with one or two shots, depending on the possibility of using longer capturing times or not. Improved TFD systems thus emerge as an interesting possibility for multispectral acquisition, which overcomes the limited accuracy found in previous studies.Spanish Ministry of Economy and Competitiveness through the research project DPI2011-2320

Increment threshold and purity discrimination spectral sensitivities of X-chromosome-linked color-defective observers

AbstractThe goal of the study was to evaluate spectral opponency in nine X-chromosome-linked color-defective observers. The tasks included increment threshold spectral sensitivity on an achromatic background, heterochromatic flicker photometry, and colorimetric purity discrimination. With a task of heterochromatic flicker photometry, the anomalous trichromatic observers showed spectral sensitivity of the corresponding dichromat. The increment threshold spectral sensitivity and colorimetric purity discrimination data were analyzed using the concept of standard cone photopigment spectral sensitivities for normal and defective vision, and a model that postulates one cone-additive and two cone-antagonistic systems. The model incorporated a shift of the peak spectral sensitivity of the long-wavelength-sensitive (LWS) pigment (for protan observers) or of the middle-wavelength-sensitive (MWS) pigment (for deutan observers). Two dichromats and two anomalous trichromats did not show clear evidence of LWS vs MWS cone antagonism. Five anomalous trichromats showed such cone antagonism. Molecular genetic analysis of the opsin genes is presented for eight of the observers

Analysis of image noise in multispectral color acquisition

The design of a system for multispectral image capture will be influenced by the imaging application, such as image archiving, vision research, illuminant modification or improved (trichromatic) color reproduction. A key aspect of the system performance is the effect of noise, or error, when acquiring multiple color image records and processing of the data. This research provides an analysis that allows the prediction of the image-noise characteristics of systems for the capture of multispectral images. The effects of both detector noise and image processing quantization on the color information are considered, as is the correlation between the errors in the component signals. The above multivariate error-propagation analysis is then applied to an actual prototype system. Sources of image noise in both digital camera and image processing are related to colorimetric errors. Recommendations for detector characteristics and image processing for future systems are then discussed