Summary: Three “wide-gamut” RGB color spaces — AdobeRGB, DCI-P3, and Rec. 2020 — are compared to the gamut of real surface colors (Pointer’s gamut) and the optimal color solid (MacAdam limits). Only Rec. 2020 covers Pointer’s gamut completely, or very nearly so, at all luminance levels examined. Rec. 2020 also approaches or exceeds the MacAdam limits in all color regions at high luminance (L* ≥ 80). Better coverage of the MacAdam limits at lower luminance levels will most likely require multi-primary displays.
Summary: The derivation of the CIE 1931 RGB color space from the Wright – Guild color matching data is described. Emphasis is placed on explaining the underlying logic of the process. The transformation of the RGB space to the CIE 1931 XYZ space is briefly described. An argument is made that the principal intent of the color matching experiments was to develop a rigorous, quantitative framework for describing all visible colors. For that purpose, negative chromaticity coefficients or imaginary primary colors are not problematic. Neither of the CIE 1931 color spaces can be displayed on a physical device; and it seems possible that little, if any, consideration was given in 1931 to practical applications of that sort. In general, digital cameras are sensitive to all visible wavelengths, and in principal can encode all humanly visible colors in raw image files. Color spaces with gamuts that exceed the AdobeRGB gamut — currently about the widest that can be reproduced on specialized displays — may be useful for processing raw images. A wide-gamut space such as ProPhotoRGB will, in theory, minimize compression of image color information during editing; thus maximizing head-room for color adjustment. Archived raw image files may also be useful in the future if very-wide gamut displays — possibly using 4, 5, or 6 primary colors — become available.
Key words: RGB color, chromaticity, W. D. Wright, J. Guild, color matching experiment, color matching function, tristimulus value, colorimetry, CIE 1931 XYZ color space, CIE 1931 RGB color space, spectral locus, imaginary color, N.P.L. Standard White Light
Summary: A Sigma DP2 Merrill and dp2 Quattro were used to photograph a 24-patch ColorChecker Classsic. Image processing (X3F and TIFF) was limited to global adjustments to white balance and exposure. Color reproduction of each of the 18 non-gray-scale patches was evaluated by comparison to the published ColorChecker (2005) L*a*b* coordinates. For both cameras, portrait color mode produced the best match to the ColorChecker. Overall, the Merrill images were a closer match to the reference values, although the difference between cameras was generally not large.
Summary: Sigma Merrill (DP1M and DP2M) and Sigma Quattro (dp1Q and dp2Q) cameras were used to make six raw image comparisons. For each pair, comparisons were made at Merrill native resolution (4,704 x 3,136) and at Quattro native resolution (5,424 x 3,616). Images were evaluated for rendition of fine detail. Quattro images were generally superior to Merrill images when the latter were up-sampled to Quattro dimensions. Images were much more closely matched when Quattro images were down-sampled to Merrill dimensions. In that case preference may be largely subjective, and perhaps significantly influenced by post-processing adjustments. Actual-pixels central-area crops are provided for each of the twelve comparisons.
Summary: A transmission step wedge was photographed with a Sigma DP1 Merrill and dp1 Quattro. Signal mean value and signal-to-noise ratio (SNR) were estimated for each color channel from the raw (X3F) files using RawDigger. Quattro raw image signal strength is substantially more uniform across color channels. Quattro images also have higher SNR (i.e., less noise) than do Merrill raw images in the red and green channels. Quattro blue channel signal strength was substantially less, and SNR was slightly inferior to that of the Merrill, particularly in the well-exposed portions of the images. Averaged across color channels, the difference in SNR is equivalent to about 1/2 EV advantage in dynamic range for the Quattro. In practice, the Quattro may have a ≥ 1 EV superiority because, in contrast to the strongly blue-channel biased overexposure of the Merrill sensor, the Quattro blue channel is relatively resistant to overexposure; and all three color channels tend to become overexposed in concert. These differences in signal strength and SNR can be understood at least partly by reference to differences in sensor design. They suggest that the Quattro design was chosen to improve signal strength and SNR in the red and green channels, while sacrificing some signal quality in the blue channel. The net effect is substantial improvement in overall signal characteristics: in particular better balance among color channels. ISO series were made with a DP2 Merrill and a dp2 Quattro. Raw files were processed through Sigma Photo Pro, exported as TIFFs, and taken into Photoshop. As expected from the signal strength and SNR analyses, Quattro images had an approximately 1-stop advantage in high ISO image quality. That is, Quattro images exposed at ISO 1600 were similar to, or slightly better than, Merrill images at ISO 800.
Summary: Larger sensors can achieve higher resolution than smaller ones only if they have more photosites. To date, the potential of full-frame sensors, in terms of image resolution, has been limited by the fact that FF sensors typically have relatively large photosites. A 36 MP FF sensor has 4.9 µm photosites, and a linear resolution of about 7,400 photosites on its long axis (3:2 aspect ratio). On the other hand, a 20 MP 1-inch sensor has 2.4 µm photosites, and a linear resolution of about 5,500 photosites on the long axis. The 35% increase in resolution provided by the FF sensor is much less than the actual difference in linear dimensions of the sensors — 172%. In order to exploit the full potential of larger sensors with respect to image resolution, it will be necessary to keep photosites small. That will involve some sacrifices in low-light performance, and entail costs in processing very large (> 100 MP) images. Also, in order to fully realize the benefits of photosite spacing of 2 – 3 µm, lenses must perform exceptionally well at f/2.8 – f/4: perhaps close to the theoretical limits set by diffraction. Assuming such FF lenses can be manufactured at reasonable cost, use of such relatively large apertures will compromise the ability to obtain appreciable depth of field while at the same time realizing increased resolution.
Summary: Photosite spacing of 1.5 µm or less is common for smart phone cameras; and 1-inch sensors in cameras such as the the Sony RX100 III have photosite spacing of 2.4 µm. Diffraction-limited line-pair resolution is given for photosite spacing as little as 0.5 µm. Two micron photosite spacing implies APS-C and “full-frame” (FF) sensors with 94 and 216 MP, respectively. In order to approach the theoretical resolution limits of sensors with 2 – 3 µm photosites, it will be necessary to have lenses that perform exceptionally well at apertures f/2.8 – f/4. It is not clear if such lenses can be manufactured at reasonable cost for APS-C and FF sensors. If it is, it may be necessary to sacrifice large maximum apertures, such as f/1.4, in order to make “slower” but sharper lenses. With current technology, 2 – 3 µm photosites will entail a trade-off between resolution and low noise, when compared to current FF and APS-C sensors. For most image uses, 100 MP or greater resolution implies capture oversampling. That is, images will be down-sampled for “final”use. It is suggested that such down-sampling may produce a sharper and less noisy final image than could otherwise be obtained by capturing images at lower initial resolution.