Performance of the euclidean color-difference formula in log-compressed OSA-UCS space applied to modified-image-difference metrics (original) (raw)
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Journal of The Optical Society of America A-optics Image Science and Vision, 2008
This work continues previous research by the same authors [J. Opt. Soc. Am. A 23, 2077], where empirical small-medium color differences were represented by an ellipsoidal equation ⌬E GP in the Uniform Color System of the Optical Society of America. Now logarithmic compressions on chroma and lightness are introduced to produce a new space with Euclidean color-difference formulas ⌬E E . The CIEDE2000, ⌬E GP , and ⌬E E formulas are found statistically equivalent in the prediction of many available empirical datasets. However, ⌬E E is the simplest formula providing relationships with visual processing. These analyses hold true for CIE 1964 Supplementary Standard Observer and D65 illuminant.
Journal of The Optical Society of America A-optics Image Science and Vision, 2006
An investigation of the color metrics and the complexity of the CIEDE2000 formula shows that CIELAB space is inadequate to represent small-medium color differences. The OSA-UCS (Uniform Color Space) Committee has shown that no space with uniform scale for large color differences exists. Therefore the practical way for color-difference specification is a color-difference formula in a nonuniform space. First, the BFD (Bradford University) ellipses are considered in the OSA-UCS space, and their very high regularity suggests a new and very simple color-difference formula at constant luminance. Then the COM (combined) data set used for the development of the CIEDE2000 formula is considered in the OSA-UCS space, and the color-difference formula is extended to sample pairs with a different luminance factor. The value of the performance factor PF/ 3 for the proposed OSA-UCS-based formula shows that the formula performs like the more complex CIEDE2000 formula for small-medium color differences.
Distance metrics for very large color differences
Color Research and Application, 2019
Small, supra-threshold color differences are typically described with Euclidean distance metrics, or dimension-weighted Euclidean metrics, in color appearance spaces such as CIELAB. This research examines the perception and modeling of very large color differences in the order of 10 CIELAB units or larger, with an aim of describing the salience of color differences between distinct objects in real-world scenes and images. A psychophysical experiment was completed to compare directly large color-difference pairs designed to probe various Euclidean and non-Euclidean distance metrics. The results indicate that very large color differences are best described by HyAB, a combination of a Euclidean metric in hue and chroma with a city-block metric to incorporate lightness differences.
New algorithm for calculating perceived colour difference of images
The Imaging Science Journal, 2006
Faithful colour reproduction of digital images requires a reliable measure to compare such images in order to evaluate the reproduction performance. The conventional methods attempt to apply the CIE Colorimetry based colour difference equations, such as CIELAB, CMC, CIE94 and CIEDE2000, to complex images on a pixel-by-pixel basis, and calculates the overall colour difference as the averaged difference of each pixel in the image. This method is simple and straightforward but often does not represent the colour difference perceived by human visual system. This paper proposes a new algorithm for calculating the overall colour difference between a reproduced image and its original. The results obtained show that this new metric provides a quantitative measure that more closely corresponds to the colour difference perceived by human visual system.
A New Spatial Colour Metric for Perceptual Comparison
researchgate.net
In this paper, we propose a new efficient full reference image quality assessment metric, which is based on human visual system proprieties in order to get the best correspondence with human judgments. The suggested full reference metric is generic (independent of image distortion type). It can be used in different application such as: compression, restoration, etc. The experimental results consider essentially JPEG2000 compressed images and ACE restored image correlate highly with the Mean Opinion Score (MOS). The correlation of the subjective ratings and objective scores illustrate the performance of the proposed metric.
Perception Based Color Image Difference
Computer Graphics Forum, 1998
A good image metric is often needed in digital image synthesis. It can be used to check the convergence behavior in progressive methods, to compare images rendered using various rendering methods etc. Since images are rendered to be observed by humans, an image metric should correspond to human perception as well. We propose here a new algorithm which operates in the original image space. There is no need for Fourier or wavelet transforms. Furthermore, the new metric is view distance dependent. The new method uses the contrast sensitivity function 8 . The main idea is to place a number of various rectangles in images, and to compute the CIE LUV average color difference between corresponding rectangles. Errors are then weighted according to the rectangle size and the contrast sensitivity function.
The prediction of perceived colour differences by colour fidelity metrics
A psychophysical experiment was conducted to evaluate the performance of various colour spaces, colour difference formulae, colour matching functions and colour fidelity measures in predicting perceived colour differences. Ten observers evaluated the colour differences of 20 colour samples under 11 pairs of light sources. The results suggest that the colour differences calculated using the CIE 1964 colour matching functions in the CAM02-UCS colour space can predict the perceived colour differences. IES-R f which used the 20 colour samples and the reference illuminants used in the experiment was highly correlated to the perceived colour difference. The importance of a uniform spectral sensitivity for colour fidelity measures is also identified.
Final program and proceedings, 1996
Color differences are almost always described by DE in Lab color space. This space, defined by the 1976 CIE report, is calculated using the Tristimulus values X, Y, Z, defined in the CIE 1931 report. Further, a complex image is often evaluated by averaging the individual ∆Es to calculate a Color Metric for the color difference between two images. The experiments in this paper generate triplets of images: one is defined as "Original" the other two as "Reproductions." Each area in the "Reproduction" differs from the "Original" by a constant ∆E. The goal of the experiments is to see if some choices of colors make better reproductions than others. The results show that color metrics comparing color differences across edges within the same image predict better reproductions than color metrics comparing absolute Lab values of corresponding areas in different images.
Multi-level contrast filtering in image difference metrics
EURASIP Journal on Image and Video Processing, 2013
In this paper, we present a new metric to estimate the perceived difference in contrast between an original image and a reproduction. This metric, named weighted-level framework E E (WLF-DEE), implements a multilevel filtering based on the difference of Gaussians model proposed by and the new Euclidean color difference formula in log-compressed OSA-UCS space proposed by . Extensive tests and analysis are presented on four different categories belonging to the well-known Tampere Image Database and on two databases developed at our institution, providing different distortions directly related to color and contrast. Comparisons in performance with other state-of-the-art metrics are also pointed out. Results promote WLF-DEE as a new stable metric for estimating the perceived magnitude of contrast between an original and a reproduction.
ECTI Transactions on Computer and Information Technology (ECTI-CIT), 1970
As CIEDE2000 standard has developed the colour difference formula, the colour difference formula of compared colours in similar colour space has been evaluated and emphasized in this paper. The lightness difference effective term has been distinctively separated from the small informative colourdifference of CIEDE2000. In addition, the power of the lightness difference effective term can clearly magnify the lightness difference which illustrated categorized surfaces of the lightness difference effective term for total colour differences in the CIEDE2000 standard. All projected four categories are classified by compared image colour pixels based on the colour space's three forward transform functions of the lightness of the colour, the chroma between red/magenta and green, and the chroma between yellow and blue. Results show that the lightness difference effective term gives mainly three different surfaces in four categories. Furthermore, in first category, the most two maximum statistical frequencies can be expressed with the left side along with the right side of the probability mass function of the lightness difference effective term; in third category, the obvious maximum statistical frequency can be expressed with only the left side of the probability mass function; and in second and fourth categories, the maximum statistical frequency can be expressed most absolutely with the left side of the probability mass function.