The interim connection space based on human color vision for spectral color reproduction

2012 ◽  
Vol 29 (6) ◽  
pp. 1027 ◽  
Author(s):  
Xiandou Zhang ◽  
Qiang Wang ◽  
Jincheng Li ◽  
Ping Yang ◽  
Jieyue Yu
Keyword(s):  
Color Vision ◽  
Color Reproduction ◽  
Human Color Vision ◽  
Connection Space

scholarly journals Weighted LabPQR Interim Connection Space Based on Human Color Vision for Spectral Color Reproduction

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Guangyuan Wu ◽  
Zhen Liu ◽  
Shengwei Yang ◽  
Ming Zhu ◽  
Pan Liu
Keyword(s):  
Weight Function ◽  
Color Vision ◽  
The Other ◽  
Weight Functions ◽  
Matching Function ◽  
Color Reproduction ◽  
Color Information ◽  
Visual Color ◽  
Human Color Vision ◽  
Connection Space

A weighted LabPQR interim connection space, based on human color vision, is proposed for retaining more visual color information. A new weight function proposed in our paper is connected with color-matching function and then further weighted the PQR dimensions of LabPQR compared with the other two weight functions and nonweight function. The results indicated that weighting obviously improved the colorimetric representing accuracy and robustness compared with nonweighting, and the new weight function outperformed the other two weight functions. The weighted LabPQR of the new weight function is most suitable for spectral color reproduction.

Bipolar or rectified chromatic detection mechanisms?

2001 ◽  
Vol 18 (1) ◽  
pp. 127-135 ◽  
Author(s):  
MARCEL J. SANKERALLI ◽  
KATHY T. MULLEN
Keyword(s):  
Color Vision ◽  
Masking Effect ◽  
Yellow Light ◽  
Detection Thresholds ◽  
Noise Masking ◽  
Human Color Vision ◽  
Early Processing ◽  
The Cross ◽  
On And Off Pathways ◽  
Luminance Increment

It is widely accepted that human color vision is based on two types of cone-opponent mechanism, one differencing L and M cone types (loosely termed “red–green”), and the other differencing S with the L and M cones (loosely termed “blue–yellow”). The traditional view of the early processing of human color vision suggests that each of these cone-opponent mechanisms respond in a bipolar fashion to signal two opponent colors (red vs. green, blue vs. yellow). An alternative possibility is that each cone-opponent response, as well as the luminance response, is rectified, so producing separable signals for each pole (red, green, blue, yellow, light, and dark). In this study, we use psychophysical noise masking to determine whether the rectified model applies to detection by the postreceptoral mechanisms. We measured the contrast-detection thresholds of six test stimuli (red, green, blue, yellow, light, and dark), corresponding to the two poles of each of the three postreceptoral mechanisms. For each test, we determined whether noise presented to the cross pole had the same masking effect as noise presented to the same pole (e.g. comparing masking of luminance increments by luminance decrement noise (cross pole) and luminance increment noise (same pole)). To avoid stimulus cancellation, the test and mask were presented asynchronously in a “sandwich” arrangement (mask-test-mask). For the six test stimuli, we observed that noise masks presented to the cross pole did not raise the detection thresholds of the test, whereas noise presented to the same pole produced a substantial masking. This result suggests that each color signal (red, green, blue, and yellow) and luminance signal (light and dark) is subserved by a separable mechanism. We suggest that the cone-opponent and luminance mechanisms have similar physiological bases, since a functional separation of the processing of cone increments and cone decrements could underlie both the separation of the luminance system into ON and OFF pathways as well as the splitting of the cone-opponent mechanisms into separable color poles.

Research Mathematical Model of Human Color Vision Characteristics Based on CRT Display

2013 ◽  
Vol 28 (3) ◽  
pp. 365-372
Author(s):  
黄新民 HUANG Xing-ming ◽  
申静 SHEN Jing ◽  
任亚杰 REN Ya-jie ◽  
姚军财 YAO Jun-cai
Keyword(s):  
Mathematical Model ◽  
Color Vision ◽  
Human Color Vision

scholarly journals Discrimination Between Explosive Materials and Isomers Using a Human Color Vision-Inspired Sensing Method

2019 ◽  
Vol 73 (5) ◽  
pp. 520-528 ◽  
Author(s):  
Kevin J. Major ◽  
Thomas C. Hutchens ◽  
Christopher R. Wilson ◽  
Menelaos K. Poutous ◽  
Ishwar D. Aggarwal ◽  
...  
Keyword(s):  
Color Vision ◽  
Optical Filters ◽  
High Confidence ◽  
Absorption Bands ◽  
Vision Sensing ◽  
Explosive Materials ◽  
Human Color Vision ◽  
Ft Ir ◽  
Aluminum Substrates ◽  
Ft Ir Spectroscopy

This paper describes the application of a human color vision approach to infrared (IR) chemical sensing for the discrimination between multiple explosive materials deposited on aluminum substrates. This methodology classifies chemicals using the unique response of the chemical vibrational absorption bands to three broadband overlapping IR optical filters. For this effort, Fourier transform infrared (FT-IR) spectroscopy is first used to computationally examine the ability of the human color vision sensing approach to discriminate between three similar explosive materials, 1,3,5,-Trinitro-1,3,5-triazinane (RDX), 2,2-Bis[(nitrooxy)methyl]propane-1,3,-diyldinitrate (PETN), and 1,3,5,7-Tetranitro-1,3,5,7-tetrazocane (HMX). A description of a laboratory breadboard optical sensor designed for this approach is then provided, along with the discrimination results collected for these samples using this sensor. The results of these studies demonstrate that the human color vision approach is capable of high-confidence discrimination of the examined explosive materials.

scholarly journals New Aspects of an Old Theme: The Genetic Basis of Human Color Vision

1998 ◽  
Vol 63 (5) ◽  
pp. 1257-1262 ◽  
Author(s):  
Bernd Wissinger ◽  
Lindsay T. Sharpe
Keyword(s):  
Color Vision ◽  
Genetic Basis ◽  
Human Color Vision

scholarly journals How long range is contour integration in human color vision?

2003 ◽  
Vol 20 (1) ◽  
pp. 51-64 ◽  
Author(s):  
WILLIAM H.A. BEAUDOT ◽  
KATHY T. MULLEN
Keyword(s):  
Color Vision ◽  
Long Range ◽  
Short Range ◽  
Contour Integration ◽  
Contour Detection ◽  
Critical Element ◽  
Element Size ◽  
Human Color Vision ◽  
The Mean ◽  
Gabor Elements

We quantified and compared the effect of element spacing on contour integration between the achromatic (Ach), red–green (RG), and blue–yellow (BY) mechanisms. The task requires the linking of orientation across space to detect a contour in a stimulus composed of randomly oriented Gabor elements (1.5 cpd, σ = 0.17 deg), measured using a temporal 2AFC method. A contour of ten elements was pasted into a 10 × 10 cells array, and background elements were randomly positioned within the available cells. The effect of element spacing was investigated by varying the mean interelement distance between two and six times the period of the Gabor elements (λ = 0.66 deg) while the total number of elements was fixed. Contour detection was measured as a function of its curvature for jagged contours and for closed contours. At all curvatures, we found that performance for chromatic mechanisms declines more steeply with the increase in element separation than does performance for the achromatic mechanism. Averaged critical element separations were 4.6 ± 0.7, 3.6 ± 0.4, and 2.9 ± 0.2 deg for Ach, BY, and RG mechanisms, respectively. These results suggest that contour integration by the chromatic mechanisms relies more on short-range interactions in comparison to the achromatic mechanism. In a further experiment, we looked at the combined effect of element size and element separation in contour integration for the Ach mechanism.

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