When viewing a reproduction of a painting in textbooks and online, important visual information, including surface
texture, can be lost. Providing an experience to viewers that can convey some of this lost information without
significantly increasing the necessary equipment and training possessed by a typical studio photographer would enrich
education, documentation, conservation, and presentation of artwork for the public. A modified photometric stereo
technique coupled with the rendering software mental ray packaged with Maya® is presented as a means of capturing
surface normal maps and diffuse color information used in the rendering of realistic attributes of paintings. mental ray’s
ability to realistically render two different paintings with different gloss properties was evaluated by comparing the
proposed capture technique and a previously published technique that employs cross-polarization, demonstrating that
traditional imaging is a viable technique for generating input data for computer graphics rendering software.
KEYWORDS: RGB color model, Optical filters, Interference (communication), Color reproduction, Sensors, Color image segmentation, Image sensors, Signal to noise ratio, Quantum efficiency, Image filtering
Filter optimization is investigated to design digital camera color filters that achieved high color accuracy and low image noise when a sensor's inherent photon shot noise is considered. In a computer simulation, both RGB- and CMY-type filter sets are examined. Although CMY filters collect more photons, performance is worse than for RGB filters in terms of either color reproduction or noise due to the large noise amplification during the color transformation. When RGB filter sets are used and photon shot noise is considered, the peak wavelength of the R channel should be longer (620 to 630 nm) than the case when only color reproduction is considered: peak wavelengths 600, 550, and 450 nm for RGB channels, respectively. Increasing the wavelength reduces noise fluctuation along the a* axis, the most prominent noise component in the latter case; however, color accuracy is reduced. The tradeoff between image noise and color accuracy due to the peak wavelength of the R channel leads to a four-channel camera consisting of two R sensors and G and B. One of the two R channels is selected according to the difference in levels to reduce noise while maintaining accurate color reproduction.
A filter optimization was investigated to design digital camera color filters that achieved high color accuracy and low image noise when accounting for a sensor's inherent photon shot noise. In the computer simulation, Gaussiantype spectral-sensitivity curves along with an IR blocking filter were used. When only color reproduction was considered, the best peak wavelengths for RGB channels were 600, 550 and 450nm, respectively, but when both color reproduction and photon shot noise were considered, the peak wavelength of the R channel should be longer (620 - 630nm). Increasing the wavelength reduced noise fluctuation along the a* axis, the most prominent noise component in the former case; however, color accuracy was reduced. The tradeoff between image noise and color accuracy due to the peak wavelength of the R channel led to a four-channel camera consisting of two R sensors and G and B. One of the two R channels was selected according to the difference in levels in order to reduce noise while maintaining accurate color reproduction.
Compared with colorimetric imaging, multispectral imaging has the advantage of retrieving spectral reflectance factor
of each pixel of a painting. Using this spectral information, pigment mapping is concerned with decomposing the spectrum into its constituent pigments and their relative contributions. The output of pigment mapping is a series of spatial concentration maps of the pigments comprising the painting. This approach was used to study Vincent van Gogh's The Starry Night. The artist's palette was approximated using ten oil pigments, selected from a large database of pigments used in oil paintings and a priori analytical research on one of his self portraits, executed during the same time period. The pigment mapping was based on single-constant Kubelka-Munk theory. It was found that the region of blue sky where the stars were located contained, predominantly, ultramarine blue while the swirling sky and region surrounding the moon contained, predominantly, cobalt blue. Emerald green, used in light bluish-green brushstrokes surrounding the moon, was not used to create the dark green in the cypresses. A measurement of lead white from Georges Seurat's La Grande Jatte was used as the white when mapping The Starry Night. The absorption and scattering properties of this white were replaced with a modern dispersion of lead white in linseed oil and used to simulate the painting's appearance before the natural darkening and yellowing of lead white oil paint. Pigment mapping based on spectral imaging was found to be a viable and practical approach for analyzing pigment composition, providing new insight into an artist's working method, the possibility for aiding in restorative inpainting, and lighting design.
Spectral separation is the process of obtaining printer control values to reproduce a given spectral reflectance. Given a multispectral image where each pixel represents a spectral reflectance, separation could be implemented by inverting a physical printer model on a pixel-by-pixel basis. Such a process would obviously need to be very fast to handle high-resolution images in a reasonable time. For a printer whose spectral response is characterized by the Yule–Nielsen spectral Neugebauer model, the linear regression iteration (LRI) method can be used to invert the model. We introduce the subspace linear regression iteration (SLRI) method, a modification of LRI shown to be significantly accelerated due to performing its calculations within the subspace determined by the Neugebauer primaries. Using this subspace approach, the number of multiplications becomes independent of the spectral sampling rate. Using a standard six color printer and a common spectral sampling rate, the number of multiplications can be decreased by about two-thirds without changing the convergence behavior.
Many art objects have a size much larger than their softcopy reproductions. In order to develop a multiscale model that
accounts for the effect of image size on image appearance, a digital projector and LCD display were colorimetrically
characterized and used in a contrast matching experiment. At three different sizes and three levels of contrast and
luminance, a total of 63 images of noise patterns were rendered for both displays using three cosine log filters. Fourteen
observers adjusted mean luminance level and contrast of images on the projector screen to match the images displayed
on the LCD. The contrasts of the low frequency images on the screen were boosted while their mean luminance values
were decreased relative to the smaller LCD images. Conversely, the contrast of projected high frequency images were
reduced for the same images on LCD with a smaller size. The effect was more pronounced in the matching of projected
image to the smaller images on the LCD display. Compared to the mean luminance level of the LCD images, a reduction
of the mean luminance level of the adjusted images was observed for low frequency noise patterns. This decrease was
more pronounced for smaller images with lower contrast and high mean luminance level.
The optimal design of spectral sensitivity functions for digital color imaging devices has been studied extensively. This paper analyzed the important requirements for designing sensor sensitivity functions. A hierarchical approach is proposed to the optimal design of camera spectral sensitivity functions by incorporating spectral fitting, colorimetric performance and noise. The approach is directly based on the filter fabrication parameters to avoid approximation deviation. A six-channel camera is designed via this approach, with the first three channels aiming at colorimetric performance and the total six channels for spectral performance.
A multi-spectral imaging symposium was held during AICO1 consisting of invited and contributed papers. An overview of visible-spectrum imaging techniques was presented by the moderator (R. Berns), described in this paper.
CIE technical committee TCl-47 was established with a goal to improve the performance of the CIE94 color-difference equation. Recent visual experiments indicated that a hue-angle dependency might exist. Four datsets focused on hue differences were used to derive a new hue-angle function. The resulting function resulted in a statistically significant improvement compared with existing color-difference equations.
A practical and easy way to capture images of oil-paintings and estimate their spectral reflectance as a function of position was tested. For the image acquisition, a trichromatic digital camera was used in conjunction with an absorption filter producing six channels. From an a priori statistical analysis of common artist oil paints, spectral reflectance was estimated. These experiments showed that it is possible to estimate the spectral reflectance with an accuracy of average ΔE*94 of 1.7 and spectral reflectance rms error of 2.2%. Of particular interest is guidance towards the design of a universal calibration target for imaging paintings.
Efforts to construct end-to-end color reproduction systems based on the preservation of scene spectral data have been underway at the Munsell Color Science Laboratory. The goal is to present hardcopy results which are spectrally matched to original colors. The evaluated approach consists of capturing scenes through a trichromatic digital camera combined with multiple filterings followed by an image processing stage and then four-color printing. The acquisition end is designed to estimate original scene spectra on a pixel-by-pixel basis based on system characteristics which takes into account the camera sensitivities as modulated by the filterings followed by an image processing stage and then four-color printing. The acquisition end is designed to estimate original scene spectra on a pixel-by-pixel basis based on system characterizations which takes into account the camera sensitivities as modulated by the filterings an scene colorant make-up. The spectral-based printing used in this research is able to produce the least metameric reproduction to the original scene using a computationally feasible approach. Results show a system accuracy of mean (Delta) E*94 of 1.5 and spectral reflectance rms error of 0.9 percent.
The traditional techniques of image capture, scanning, proofing, and separating do not take advantage of colorimetry and spectrophotometry. For critical color-matching applications such as catalog sales, art-book reproductions, and computer-aided design, typical images, although pleasing, are unacceptable with respect to color accuracy. The limitations that lead to these errors have a well-defined theoretical basis and are a result of current hardware and software. This has led us to a re-examination of the traditional graphic reproduction paradigm. A research and development program has begun that will alleviate the theoretical limitations associated with traditional techniques. There are four main phases: (1) Multi-spectral image capture, (2) Spectral-based separation and printing algorithm development, (3) Implementation on press, and (4) Systems integration with data and image archives. This paper describes this new paradigm, summarizes recent research results, and considers implementation opportunities.
The color-image quality of color overhead transparencies depends on properties of the imaging system used to create the transparency and illuminating and viewing conditions of the transparency such as the projector's spectral power distribution, projector distance from the screen, and luminance, ambient lighting, screen gonio-spectral reflectance factor, and viewing distance and geometry. As different visual fields and/or luminance of those fields, some of these illuminating and viewing conditions can be taken into suitable
account using color-appearance models. A visual experiment is performed to determine whether color-appearance correlates of visual perception could be used to predict color-image quality for this
imaging modality. The Hunt 1991 color-appearance model is used to define correlates of hue, brightness, colorfulness, lightness, and chroma for both pictorial and business-graphic scenes viewed under several combinations of ambient illuminance and projector luminance. Gamut volume is defined based on either absolute attributes-hue, brightness, and colorfulness-or relative attributes-hue, lightness, and chroma. Seventeen observers performed a preference experiment generating interval scales of color-image quality. It is found that gamut volume defined by using correlates of hue, brightness, and colorfulness well predicted color-image quality. Of these correlates, colorfulness was the most important factor.
KEYWORDS: CRTs, RGB color model, Projection systems, Transmittance, Color reproduction, Image processing, Performance modeling, Data modeling, 3D modeling, Imaging systems
Accurate color reproduction of images presented on a
computer-controlled CRT display as projected 35-mm transparencies is a complicated procedure requiring the characterization and control of several imaging processes and the application of appropriate color appearance modeling to account for the changes in viewing conditions. We review a process for image recorder characterization, projection system characterization, and testing of color appearance models for this application. Accurate image recorder characterization was achieved through a combination of empirical modeling of the exposure and processing system and of a physical model of photographic film. The projection system characterization included specification of the spectral properties of the light source, reflectance properties of the viewing screen, and the effects of light exposure and temperature on the photographic transparencies. Color appearance models were used to predict the changes in image color appearance due to changes in media, white point, luminance, and surround. The RLAB model proved to work best in this application.
Color-appearance models are used to relate chromatic
stimuli viewed under one set of viewing and illuminating conditions to a differing set such that when each stimulus is viewed in its respective conditions, the stimuli match in color appearance. These models assume the observer has a steady-state adaptation to each condition. In practice, observers often view stimuli under mixed adaptation; this could occur when viewing CRT and reflection-print stimuli simultaneously. A visual experiment was performed to determine whether the RLAB color-appearance model could be used successfully to generate reflection prints that match the appearance of the CRT when viewed under mixed states of adaptation and in turn
as stand-alone images viewed under a single state of adaptation. Sixteen observers viewed four pictorial images displayed on a D65 balanced CRT display in a room lit with cool-white fluorescent luminaries.
The RLAB color-appearance model was used to calculate
corresponding images where the observer's state of chromatic adaptation was assumed to be one of the following: adaptation to each device condition, a single adaptation at the midpoint of the two device
conditions, adaptation to the CRT condition and a print adaptation shifted 25% toward the CRT condition, adaptation to the print condition and a CRT adaptation shifted 25% toward the print condition, and a CRT condition shifted 25% toward the print condition and a print condition shifted 25% toward the CRT condition. Each condition was compared pairwise and Thurstone's law of comparative
judgments was used to calculate interval scales of quality. Observers first judged the reflection prints adjacent to the CRT display selecting the image closest in color appearance to the CRT image; they also categorized the closest image as "acceptable, " "marginally acceptable, " or "not acceptable. " The images were again scaled except the display was turned off; this determined the best standalone color reproduction...
A desktop drum scanner was colorimetrically characterized to an average CIELAB error of less than unity for Kodak Ektachrome transparencies and Ektacolor paper, and Fuji Photo Film Fuflchrome transparencies and Fujicolor paper. Independent verification on spectrally similar materials yielded an average z Eb error of less than 2. 1. The image formation of each medium was first modeled using either Beer-Bouguer or Kubelka-Munk theories and
eigenvector analysis. Scanner digital values were then empirically related to dye concentrations using polynomial step-wise multiplelinear regression. These empirical matrices were required because the scanner's system spectral responsivities had excessively wide bandwidths. From these estimated dye concentrations, either a spectral transmittance or spectral reflectance factor was calculated from an a priori spectral analysis of each medium. The spectral estimates can be used to calculate tristimulus values for any illuminant and obseiver of interest. The methods used in this research are based on historical methods commonly used in photographic science.
A model was derived and tested that predicted the spectral reflectance factor from digital data for a dye diffusion thermal transfer printer. The model was based on the Kubelka-Munk turbid media theory and included terms to account for back diffusion onto
the donor supply and dye transfer inhibition. The average colonmetric characterization accuracy of the printer's color gamut based on 45 samples to estimate the model parameters was 3.0 Eb with a maximum of 7.4. The spectral model had similar performance to look-up table and multidimensional interpolation methods and supenior performance to multiple-linear regression methods based on tristimulus data.
KEYWORDS: Transparency, Printing, Visualization, Scanners, RGB color model, Image compression, Color reproduction, CMYK color model, 3D modeling, Photography
Color gamut mapping is required whenever two imaging devices do not have coincident color gamuts or viewing conditions. Two major gamut mapping techniques include lightness and chroma manipulations. Lightness mapping accounts for differences in white level, black level, and viewing conditions while chroma mapping accounts for differences in gamut volume. As a three dimensional space in which color gamut mapping is implemented, the 1991 Hunt model of color appearance was used utilizing dimensions of lightness, chroma, and hue. This model accounts for viewing conditions in addition to the usual device independent specification. The mapping techniques were applied to back-lit photographic transparencies in order to reproduce images using a dye diffusion thermal transfer printer. As the first experiment, a lightness mapping experiment was performed. Three different lightness mapping techniques, a linear technique and two non-linear techniques, were tested for four images. The psychophysical method of paired comparison was used to generate interval scales of preferred color reproduction. In general, the preferred technique depended on the amount of lightness mapping required and on the original image's lightness histograms. For small amounts of compression, the preferred technique was a clipping type. For large amounts of compression, the preferred technique was image dependent; low preference was caused by loss of detail or apparent fluorescence of high chroma image areas.
This paper describes a visual experiment in which a group of observers made forced choice judgments of the location of neutral in test images presented on a color CRT display and photographic reflection prints. The CRT and photographic images were presented both separately and side-by-side in a simulated office environment under two conditions of ambient illumination, tungsten and daylight fluorescent. The results indicate that an observer's state of chromatic adaptation during image viewing is mainly dependent on image areas with little or no dependence upon the surrounding environment. With reflection images viewed in normal conditions, observers were noted to automatically discount ambient illumination. When viewing self-luminous images however, observers formed relative judgements only under certain conditions. These results are discussed in terms of their use in choosing white points for color reproduction calculations.
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