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Grey level and noise evaluation of a Foveon X3 image sensor: a statistical and experimental approach.

Riutort-Mayol G, Marqués-Mateu A, Seguí AE, Lerma JL - Sensors (Basel) (2012)

Bottom Line: A practical, comprehensive and flexible procedure to analyze the radiometric values and the uncertainty effects due to the camera sensor system is described in this paper.The presented linear model integrates all the individual sensor noise sources in one global component and characterizes the radiometric values and the uncertainty effects according to the influential factors such as the scene reflectance, wavelength range and time.It is confirmed the flexibility of the procedure to model and characterize the radiometric values, as well as to determine the behaviour of two phenomena when dealing with image sensors: the noise of a single image and the stability (trend and noise) of a sequence of images.

View Article: PubMed Central - PubMed

Affiliation: Department of Cartographic Engineering, Geodesy and Photogrammetry, Universitat Politècnica de València, Valencia 46022, Spain. gabriuma@upv.es

ABSTRACT
Radiometric values on digital imagery are affected by several sources of uncertainty. A practical, comprehensive and flexible procedure to analyze the radiometric values and the uncertainty effects due to the camera sensor system is described in this paper. The procedure is performed on the grey level output signal using image raw units with digital numbers ranging from 0 to 2(12)-1. The procedure is entirely based on statistical and experimental techniques. Design of Experiments (DoE) for Linear Models (LM) are derived to analyze the radiometric values and estimate the uncertainty. The presented linear model integrates all the individual sensor noise sources in one global component and characterizes the radiometric values and the uncertainty effects according to the influential factors such as the scene reflectance, wavelength range and time. The experiments are carried out under laboratory conditions to minimize the rest of uncertainty sources that might affect the radiometric values. It is confirmed the flexibility of the procedure to model and characterize the radiometric values, as well as to determine the behaviour of two phenomena when dealing with image sensors: the noise of a single image and the stability (trend and noise) of a sequence of images.

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Related in: MedlinePlus

Sttr vs. time interval factor I, according to the reflectance factor R or radiometric value factor F, equivalently.
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f12-sensors-12-10339: Sttr vs. time interval factor I, according to the reflectance factor R or radiometric value factor F, equivalently.

Mentions: The resulting ANOVA table is shown in Table 7. The effect of the radiometric value factor f is not significant. This only has some significance when interacting with the time interval factor I. Eliminating the clear non-significant effects, that is, the effect of the interaction between the spectral response S(λ) and the radiometric values f and the effect of the triple interaction between spectral response S(λ), time interval I and the radiometric values f, and adjusting the model again, a new resulting ANOVA table is obtained (Table 8). The effect of the radiometric value factor f is not statistically significant, but its interaction effect with the time interval factor I has some significance. In the time interval of 15 s some variability due to the reflectance factor or radiometric value factor exists as can be seen in Figure 12. Nevertheless, this variability is quite small and we can consider that the radiometric value factor does not affect the Sttr.


Grey level and noise evaluation of a Foveon X3 image sensor: a statistical and experimental approach.

Riutort-Mayol G, Marqués-Mateu A, Seguí AE, Lerma JL - Sensors (Basel) (2012)

Sttr vs. time interval factor I, according to the reflectance factor R or radiometric value factor F, equivalently.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472831&req=5

f12-sensors-12-10339: Sttr vs. time interval factor I, according to the reflectance factor R or radiometric value factor F, equivalently.
Mentions: The resulting ANOVA table is shown in Table 7. The effect of the radiometric value factor f is not significant. This only has some significance when interacting with the time interval factor I. Eliminating the clear non-significant effects, that is, the effect of the interaction between the spectral response S(λ) and the radiometric values f and the effect of the triple interaction between spectral response S(λ), time interval I and the radiometric values f, and adjusting the model again, a new resulting ANOVA table is obtained (Table 8). The effect of the radiometric value factor f is not statistically significant, but its interaction effect with the time interval factor I has some significance. In the time interval of 15 s some variability due to the reflectance factor or radiometric value factor exists as can be seen in Figure 12. Nevertheless, this variability is quite small and we can consider that the radiometric value factor does not affect the Sttr.

Bottom Line: A practical, comprehensive and flexible procedure to analyze the radiometric values and the uncertainty effects due to the camera sensor system is described in this paper.The presented linear model integrates all the individual sensor noise sources in one global component and characterizes the radiometric values and the uncertainty effects according to the influential factors such as the scene reflectance, wavelength range and time.It is confirmed the flexibility of the procedure to model and characterize the radiometric values, as well as to determine the behaviour of two phenomena when dealing with image sensors: the noise of a single image and the stability (trend and noise) of a sequence of images.

View Article: PubMed Central - PubMed

Affiliation: Department of Cartographic Engineering, Geodesy and Photogrammetry, Universitat Politècnica de València, Valencia 46022, Spain. gabriuma@upv.es

ABSTRACT
Radiometric values on digital imagery are affected by several sources of uncertainty. A practical, comprehensive and flexible procedure to analyze the radiometric values and the uncertainty effects due to the camera sensor system is described in this paper. The procedure is performed on the grey level output signal using image raw units with digital numbers ranging from 0 to 2(12)-1. The procedure is entirely based on statistical and experimental techniques. Design of Experiments (DoE) for Linear Models (LM) are derived to analyze the radiometric values and estimate the uncertainty. The presented linear model integrates all the individual sensor noise sources in one global component and characterizes the radiometric values and the uncertainty effects according to the influential factors such as the scene reflectance, wavelength range and time. The experiments are carried out under laboratory conditions to minimize the rest of uncertainty sources that might affect the radiometric values. It is confirmed the flexibility of the procedure to model and characterize the radiometric values, as well as to determine the behaviour of two phenomena when dealing with image sensors: the noise of a single image and the stability (trend and noise) of a sequence of images.

No MeSH data available.


Related in: MedlinePlus