luminance difference
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2019 ◽  
Vol 9 (20) ◽  
pp. 4471
Author(s):  
Jianhua Ding ◽  
Qi Yao ◽  
Lei Jiang

Despite the fact that a 2-degree spectral sensitivity curve (SSC) is extensively used in scientific research and relevant applications, the choice between the 10-degree or the 2-degree photopic SSCs in practical applications for the calculation of scotopic/photopic ratios (S/P ratios) depends on actual needs. We examined S/P ratios for more than 300 light sources for correlated colour temperatures (CCTs) from 2000 K to 8000 K and blackbody radiant spectra from 10000 K to 45000 K using 2- and 10-degree SSCs. Results showed that the ratio of the S/P values calculated using the 10-degree and 2-degree SSCs was approximately equal to 0.916. The average mesopic luminance difference increased from 0% to 5.7% at a photopic adaptation luminance from 0.005 to 5 cd/m2. For most practical applications, the mesopic luminance values calculated using these two SSCs were different by several percentage units, yet these differences could be neglected. At extremely high CCTs over 10000 K, the mesopic luminance difference may approximate the maximum value of 16%. This work proposes the conversion coefficients for S/P ratios and the transforming mesopic luminance values calculated for 2- and 10-degree SSC systems. These results may help researchers clarify differences between the S/P ratios calculated using different SSCs.


2019 ◽  
Author(s):  
William Turner ◽  
Daniel Feuerriegel ◽  
Milan Andrejevic ◽  
Robert Hester ◽  
Stefan Bode

To navigate the world safely, we often need to rapidly ‘change our mind’ about decisions. Current models assume that initial decisions and change-of-mind decisions draw upon common sources of sensory evidence. In two-choice scenarios, this evidence may be ‘relative’ or ‘absolute’. For example, when judging which of two objects is the brightest, the luminance difference and luminance ratio between the two objects are sources of ‘relative’ evidence, which are invariant across additive and multiplicative luminance changes. Conversely, the overall luminance of the two objects combined is a source of ‘absolute’ evidence, which necessarily varies across symmetric luminance manipulations. Previous studies have shown that initial decisions are sensitive to both relative and absolute evidence; however, it is unknown whether change-of-mind decisions are sensitive to absolute evidence. Here, we investigated this question across two experiments. In each experiment participants indicated which of two flickering greyscale squares was brightest. Following an initial decision, the stimuli remained on screen for a brief period and participants could change their response. To investigate the effect of absolute evidence, the overall luminance of the two squares was varied whilst either the luminance difference (Experiment 1) or luminance ratio (Experiment 2) was held constant. In both experiments we found that increases in absolute evidence led to faster, less accurate initial responses and slower changes of mind. Change-of-mind accuracy decreased when the luminance difference was held constant, but remained unchanged when the luminance ratio was fixed. The initial response effects could be explained by the presence of input-dependent noise within the decision process, varying either within or across trials. However, the change-of-mind effects could not be captured by existing models, nor by two modified models which included input-dependent noise sources. This suggests that that the continued integration of sensory evidence following an initial decision operates differently to that described in existing theoretical accounts.


2013 ◽  
Vol 09 (03n04) ◽  
pp. 1350016
Author(s):  
YUANYUAN XU ◽  
BIN KONG ◽  
HU WEI ◽  
QIANG TIAN

In intelligent vehicle system, it is significant to detect and identify road markings for vehicles to follow traffic regulation. This paper proposes a method to recognize direction markings on road surface, which is on the basis of detected lanes and uses Hu moments. First of all, the detection of lanes is based on horizontal luminance difference, which converts the RGB color image to the luminance image, calculates the horizontal luminance difference, obtains the candidate points of lanes' edge and uses least square method to fit the lanes. Secondly, with the detected lines as guide for the search of candidate marking, the paper extracts Hu moments of candidate marking, calculates its Mahalanobis distance to every marking type and classifies it to the type which has the minimal distance with the candidate marking. From the simulation results, the method to detect lanes is more effective and time-efficient than canny or sobel edge detection methods; the method to recognize direction marking is effective and has a high accuracy.


2013 ◽  
Vol 380-384 ◽  
pp. 955-958
Author(s):  
Dong Yan Wu ◽  
Jian Dong Cao ◽  
Yi Jin

The luminance difference is one of the important factors of stereoscopic television. In this paper, according to the characteristics of stereoscopic television glasses, we use white window signal and black field signal to measure luminance difference of 3D TV. We adopt the left and right eye channel individually tested brightness. We chose the center point of stereoscopic television as measuring point. And then, we select a few of stereoscopic television as testing model. The proposed method may be helpful for the quality evaluation of stereoscopic television.


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