J-M Deniel : Radioprotection 2024 , 59 ( 4 ), 327 – 337 333
Table 4 . Picture definition effects on form factors and irradiance estimation from cut-out silhouette . Only p pixels corresponding to incandescent materials are considered here .
Definition Difference with 4,6403,472 px
P Width
Height p ff p E IR D P p ff p D E IR px px sr W / m 2
4,640 |
3,472 |
0.032328 |
1,196 |
( original picture ) |
|
2,320 |
1,736 |
0.030887 |
1,119 |
�3.89 % |
�6.44 % |
1,160 |
868 |
0.029056 |
1,030 |
�872 % |
�13.88 % |
580 |
434 |
0.028038 |
979 |
�11.67 % |
�18.14 % |
290 |
217 |
0.027737 |
945 |
�12.60 % |
�20.99 % |
145 |
109 |
0.030471 |
1,024 |
�4.89 % |
�14.38 % |
73 |
55 |
0.035891 |
1,122 |
þ11.06 % |
�6.19 % |
Table 5 . Chromatic noise effect on S p ff p and E IR estimation . The right columns shows the relative differences with the original picture . Noise Difference with orig . pic .
� p ff p E IR D P p ff p DE IR % sr W / m 2
|
0.049255 |
1,832 |
( original picture ) |
|
2 % |
0.051889 |
2,822 |
5.35 % |
54.04 % |
5 % |
0.052241 |
2,588 |
6.06 % |
41.27 % |
10 % |
0.052596 |
2,513 |
6.78 % |
37.17 % |
15 % |
0.052654 |
2,470 |
6.90 % |
34.83 % |
20 % |
0.052602 |
2,406 |
6.80 % |
31.33 % |
resolution image . These phenomena explain the difference between X ff p and E IR at full and lower resolutions in
p
Tables 3 and 4 .
3.5 Chromatic noise in picture effects on irradiance estimation
Sensor readings are necessarily noisy for several reasons like sensor temperature and analogic-to-digital conversion ( Davenport et al ., 2012 ; Zonios , 2010 ). Cameras can get hot and affordable ones are not cooled . We assume that readout noise influences pixels color , hence the irradiance estimation .
In the case of color cameras , this is called chromatic noise : supernumerary counts appear independently on each pixel color channel and alter its color . We showed in ( Deniel , 2024 ) that each m material at T temperature corresponds to ( g / r ; b / r ) coordinates in precomputed hue-to-exposure , T and m matrices . As chromatic noise will distort these coordinates , picture analysis accounts for the worst case in the ± 0.02 ± 0.02 matrix area around ( g / r ; b / r ).
To measure the influence of noise on estimated irradiance , we applied the Gimp RGB noise filter ( The Gimp project , n . d .) on the 1,000celsius metal furnace picture . Filter parameters are “ Independant RGB ”, “ Linear RGB ” and “ Gaussian distribution ”. The filter level varied from 2 % to 20 %. Results are given in the left part of Table 5 : they consist of the sum of form factors for all relevant pixels and to E IR . In the right part of the table , they are compared to those associated with the original picture .
As shown in the matrix exposed in the previous paper ( Deniel , 2024 ), g / r ∈ [ 0.39 ; 0.82 ] and b / r ∈ [ 0.05 ; 0.14 ]. Any supernumerary count will tend to influence temperature estimation : – on the red channel , it will tend to underestimation , – on the green and blue channel , it will tend to overestimation .
Since the red counts exceed green counts , and green counts exceed blue ones , and b / r range is the narrowest , any supernumerary count will have the highest influence when appearing on the blue channel , then on the green then on the red . Noise appearing equally on the three color channels , it will tend to overestimating material temperature , as shown in Table 5 . We can conclude that our method is conservative as chromatic noise tends to overestimate the irradiance to which workers are subjected .
4 Discussion
4.1 Consistency of irradiance between the black body and the method proposed
First , it is important to evaluate the integral difference of irradiance over [ 780 ; 3000 nm ] ( our method ) and over [ 1000 ; 2500 nm ] ( measurements ). Comparing columns E th and E IR , th