The effect of image size on the color appearance of image reproductions

Original and reproduced art are usually viewed under quite different viewing conditions. One of the interesting differences in viewing condition is size difference. The main focus of this research was investigation of the effect of image size on color perception of rendered images. This research had several goals. The first goal was to develop an experimental paradigm for measuring the effect of image size on color appearance. The second goal was to identify the most affected image attributes for changes of image size. The final goal was to design and evaluate algorithms to compensate for the change of visual angle (size). To achieve the first goal, an exploratory experiment was performed using a colorimetrically characterized digital projector and LCD. The projector and LCD were light emitting devices and in this sense were similar soft-copy media. The physical sizes of the reproduced images on the LCD and projector screen could be very different. Additionally, one could benefit from flexibility of soft-copy reproduction devices such as real-time image rendering, which is essential for adjustment experiments. The capability of the experimental paradigm in revealing the change of appearance for a change of visual angle (size) was demonstrated by conducting a paired-comparison experiment. Through contrast matching experiments, achromatic and chromatic contrast and mean luminance of an image were identified as the most affected attributes for changes of image size. Measurement of the extent and trend of changes for each attribute were measured using matching experiments. Proper algorithms to compensate for the image size effect were design and evaluated. The correction algorithms were tested versus traditional colorimetric image rendering using a paired-comparison technique. The paired-comparison results confirmed superiority of the algorithms over the traditional colorimetric image rendering for the size effect compensation

Pigment selection using Kubelka-Munk Turbid media theory and non-negative least square technique

This report describes a process of pigment selection for reconstructing the Gamblin Conservation Colors and various artist pigments dispersed in linseed oil. Single constant Kubelka–Munk (K-M) turbid media theory and a non-negative least square (NNLS) optimization technique were employed in this experiment. Eleven pigments were selected as representative of the 30-pigments Gamblin Conservation Colors. These were quinacridone red (PV 19), venetian red (PR 101), cadmium red medium (PR 108), cadmium yellow medium (PY 37), indian yellow (PY 83), chromium oxide green (PG 17), phthalocyanine green (PG 7), phthalocyanine blue (PB 15:2), cobalt blue (PB 28), titanium dioxide white (PW 6), and ivory black (PBK 9)

A prototype calibration target for spectral imaging

A prototype calibration target was designed and tested for spectral imaging that consisted of 14 samples, nine of which were derived from statistical analyses of artist paints and a five-step grey scale. This target was compared with those commonly used when calibrating spectral-imaging systems. An Esser TE221 scanner target, GretagMacbeth ColorChecker DC, GretagMacbeth ColorChecker Color Rendition Chart, and the prototype target were used as both calibration and verification targets using a modified commercial color-filter-array digital camera as a spectralimaging device. When evaluating a verification target made from 30 different pigments, the prototype target had equivalent performance. Thus for spectral imaging, the spectral properties are more important than the number of samples or its colorimetric range of colors

Using the Matrix R method for spectral image archives

Conventional color digital cameras can only produce three-channel images so they are limited when high-quality color reproduction is required. Alternatively, spectral imaging increases the number of channels and can retrieve spectral reflectance for each scene pixel. The major goal of spectral imaging is high spectral accuracy, while it may also be beneficial to achieve high colorimetric accuracy for a specific viewing condition. A new spectral reconstruction method, called the matrix R method, was developed to achieve both goals simultaneously. An experiment was performed to test this method. The experimental results have been very promising; average color difference for all targets evaluated was about 1.3 CIEDE2000 and 2.0% RMS. These results suggest that this new method is a promising method for building digital image databases for museums, archives and libraries

Spectral imaging using a commercial colour-filter array digital camera

A multi-year research programme is underway to develop and deliver spectral-based digital cameras for imaging cultural heritage at the National Gallery of Art, Washington DC, and the Museum of Modern Art, New York. The cameras will be used for documentation, production imaging, and conservation science. Three approaches have undergone testing: a liquid-crystal tunable filter (LCTF) coupled with a monochrome camera, a six-position filter wheel containing absorption filters coupled with a monochrome camera, and a two-position filter slider containing absorption filters coupled with a colour-filter array (CFA) colour camera. The last approach is the most practical as it uses conventional digital photography methodologies and equipment and can easily be incorporated into existing museum workflows. A virtual camera model was created that predicted camera signals from incident radiation and was used to design a pair of absorption filters. The filters were fabricated and tested using a commercial CFA digital camera. Our first experiments have been very promising: Average accuracy was under 1 CIEDE2000 and about 1.5 per cent RMS for both calibration and verification data. This level of performance was superior to our other, more complex approaches

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

Methods of spectral reflectance reconstruction for a sinarback 54 digital camera

There is an urgent need to build digital image databases with adequate colorimetric accuracy for museums, achieves and libraries. Traditional colorimetric imaging suffers from the possibilities of metameric problem, while spectral imaging can facilitate accurate tristimulus estimation and possibilities for spectral reconstruction of each pixel. Spectral image archives can be used to render accurate images both spectrally and colorimetrically to the original target for any illuminant and observer. The most convenient and practical capture system for spectral imaging combines a commercial trichromatic camera with two absorption filters to define image spectrally. Two images were taken for each target; so six-channel multichannel images were obtained. Three methods of spectral color reproduction were evaluated: pseudoinverse method, canonical correlation regression (CCR), and Matrix R method. The CCR method can obtain the highest spectral accuracy among these methods, just because it incorporates fifteen cross product terms in the simulation. The Matrix R method can reach the same spectral accuracy as the pseudoinverse method, and the spectral accuracy of both methods could be improved if they also use the same cross product terms. On the other hand, the Matrix R can achieve the best colorimetric accuracy for a certain combination of illuminant and observer. Thus, the Matrix R is a very promising method for achieving artwork images with sufficient spectral and colorimetric accuracy

Technical Report Gain Measurement of the Sinarback 54 Digital Camera

The camera gain of a Sinarback 54 digital camera was measured and found to be 6.0 electrons / digital count. The camera is designed in such a way that it can use 98 % of the nominal full well capacity of its CCD. A linear relationship was found between integration times and mean digital counts of dark current images. 2

Spectral Imaging Target Development Based on Hierarchical Cluster Analysis

Agglomerative hierarchical cluster analysis was used to group similar spectra from a large database of samples. Based on angles between reflectance vectors of members of a cluster, a reflectance vector was selected as representative of that cluster. Representative samples were grouped together and stored as new calibration targets. Simulated wide-band imaging with glass filters was performed using these new calibration targets and a transformation matrix from digital signals to reflectance was derived. Different verification targets were reconstructed using the transformation matrix; the spectral and colorimetric accuracy of the reconstruction was evaluated. It was shown that beyond a threshold number of samples in the calibration target, the performance of reconstruction became independent of the number of samples used in the calculation. The average spectral RMS for a calibration target consisting of 24 samples selected based on clustering were found to be less than 3.2 % fo

Principal Investigator

An investigation is proposed into the effect image size has on color appearance of softcopy reproductions. Summer support for a student stipend is requested. Original and reproduced art are usually viewed under different viewing conditions. One of the interesting differences in viewing condition is size difference. Many art objects have a size much larger than their reproductions, whether displayed on a monitor or in print. In order to develop a fundamental understanding of the effect of image size on color appearance, a digital projector and LCD display were used in a series of psychophysical experiments. It is proposed to further explore achromatic and chromatic contrast matching between different sized images with the goal of developing a model capable of accounting for the “size effect ” on color appearance