Centre de Visió per Computador - Universitat Autònoma de Barcelona

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Camera Calibration Methods (Cont.)

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Estimating the sensor's spectral sensitivities

Once we had an hint of the relationship between the camera's grey-levels and the Energy flux falling on the sensor, we measured the sensor's spectral sensitivity functions S(λ). To do this, we arranged a simple set-up that allowed us to photograph (and measure with the spectroradiometer) the light reflected from a white surface, passing though individual narrowband interference filters (which belong to a set spanning the whole visible spectrum). By comparing the output of the camera (representing energy flux) and the spectroradiometric measurements, (from which we can also estimate the correspoding energy flux) we found the camera's response to light as a function of wavelength.

A simple trichromatic camera model

Camera ModelThe figure on the left shows a schematic view of the positioning of our spectroradiometer, the light source and the target device. The light source was a modified slide projector fitted with a tungsten-halogen lamp (Osram HLX 64657FGX-24V, 250W). The projector was supplied with constant current (10.00 Amp) provided by a customised power supply  (accurate to 30 parts per million in current). In front of the light source there was an Infra-red blocking filter (B+W UV/IR blocking filter 486), to remove all possible traces of IR light from the source. The target was inside a black box with two holes (as seen from the top in the figure). One of the holes was used to let the light from the light source enter the box and the other was used to collect the light reflected from the target at back of the box. The target itself consisted of a thick layer of Cyanoacrylate adhesive powder (Kodak-Eastman "standard white" of 99% reflectance across the visible spectrum) which has a diffuse (Lambertian) pattern of reflection.

The spectral radiance of the light source and the transmittance of the 31 narrowband interference filters was measured in 1nm steps using this same setup. They span the whole visible spectrum with peaks spaced approximately 10nm and half-bandwidths of less than 5 nm each.

To calculate the energy flux present at the sensor's level, we measured the radiant power (in W.m-2.nm-1.sr-1) and converted it to Joules m-2 using the formula:

Captured energy   :Equation 5

where R(l) is the spectral transmittance of the filter, I(l) is the spectral radiant power as measured by the spectroradiometer, l represents wavelength, w is the solid angle determined by the camera's aperture and focal length and T is the integration time. All camera-dependent constants were estimated either from the camera's manufacturer's specifications or obtained from the picture's header.

The energy flux actually captured by each sensor is just the above as sampled by the specific sensor's sensitivity. In our calculations we used equations in the discrete form, that is:

Energy flux captured by each sensor   :Equation 6

where R, G and B represent the total energy flux captured by each sensor during exposure time T. In the previous equation, all variables are known except Sr,g,b(l), the sensors' spectral sensitivities.

From our previous measures we established that the camera output in grey-levels has a given dependency of light intensity, which expressed for all three sensors has the form:

sensor's gamma functions   :Equation 7

where r, g and b are grey-levels of each sensor, R, G and B the energy flux, and a, b and c are the corresponding constants for each sensor.

Combining Equations 6 and 7 we get:

greylevels as a function of all other parameters   :Equation 8

which is a description of the grey-level values obtained as a funtion of all other varaibles and paramenters. In Equations 8, all parameters a, b, c, and d are unknown but can be approximated from those in Equation 4. We also don't know the shapes of the sensor's sensitivities S(l).

To obtain the unknown parameters of equations 8 we compared the r, g, b values from Equation 8 to those obtained from the original set of 31 photographs (taken though each of the monochromatic filters) and the Macbeth Color-Checker pictures (one rgb triplet for each Color-Checker square). We will refer to these values as r_hat g_hat and b_hat. By minimizing the differences between these (see equation below) we converge to a set of optimal parematers that explain our results.

least squares minimisation   :Equation 9

As a first approximation, we modeled the sensor's sensitivities S(l) as a set of Gaussians whose free parameters were height, peak position and width. The initial a. b, c and d values were those obtained for the luminance case. The values epsilonr,g,b in Equation 9 were minimised, comparing those obtained while photographing the Macbeth card and the chromatically filtered white target (r_hat g_hat and b_hat) with those obtained theoretically through equation 8 ( r, g, b). From the fitting algorithm we found both the parameters of the equation 7 and the sensitivities S(l) of equation 6.

Figure 2 below shows a comparison of the energy flux calculations across the spectrum (31 narrowband filters) using the two methods, radiometrically-based and model-based. Both estimates reach good agreement considering the error bars (based on the StdDev of the grey-level counts r,g,b).

To obtain the agreement shown in Figure 2, the shape of S(l) was modified from the original Gaussians (for each colour channel) allowing each point to fluctuate a fixed percentage around the starting values. Figure 3 below shows the final shape of the sensor sensitivity functions, SR(l), SG(l) and SB(l), obtained after being adjusted so that equations 9 are minimised. The parameters obtained from the fittings were:

 

a

b

c

d

red

1.3176.10-7

1.1949

-2.503·10-4

-601.7059

green

1.7044.10-7

1.2603

-4.2848·10-4

-911.0773

blue

1.9233.10-7

1.2671

-3.2769.10-4

-680.8141

and now it is possible to confirm the relationship between the grey-level output (r,g,b) and the energy flux on the sensors. The results can be seen below (Figure 4, Figure 5 and Figure 6) for the red, green and blue sensors respectively.

1. A schematic view of the "target" For our purposes, we built a system which consisted of a black box with two holes, a frontal hole to let the light through and a side hole to measure (or photograph) the light reflected from its back wall (target). The target was a white diffuse reflecting substance: a thick layer of Cyanoacrylate adhesive powder (Kodak-Eastman "standard white" of 99% reflectance across the visible spectrum)

Camera Model

2. The Photon countThe camera model and the Spectroradiometer allow us tomeasure the energy flux at any wavelength. This plot shows a comparison between both results. The model's parameters were adjusted to fit the radiometric results. Error bars show the uncertainty derived from the variation of pixel grey-level values at the centre of the target. Spectroradiometric measures had a maximum 3% error (at extreme wavelengths)Camera Model

3. Sensor's spectral sensitivity The sensor's sensitivities were initially modeled as a set of parameterised Gaussian functions. They were later allowed to fluctuate to fit the spectroradiometric data.

Camera Model

4. Predicted and measured R sensor values A comparison between predicted and measured values for the red sensor. The abscissa shows all the grey-level values (obtained from all Macbeth card pictures and chromatically filtered pictures) against the energy flux calculated from the corresponding Spectroradiometric measures (Equation 6). The black line is our model's adjustment (Equations 8). Errors bars were derived from the StdDev of the averaged pixel regions at the centre of each square and the estimated 5% error of the measuring device.

Camera Model

5. Predicted and measured G sensor valuesA comparison between predicted and measured values for the green sensor. The abscissa shows all the grey-level values (obtained from all Macbeth card pictures and chromatically filtered pictures) against the energy flux calculated from the corresponding Spectroradiometric measures (Equation 6). The black line is our model's adjustment (Equations 8). Errors bars were derived from the StdDev of the averaged pixel regions at the centre of each square and the estimated 5% error of the measuring device.

Camera Model

 

6. Predicted and measured B sensor values A comparison between predicted and measured values for the blue sensor. The abscissa shows all the grey-level values (obtained from all Macbeth card pictures and chromatically filtered pictures) against the energy flux calculated from the corresponding Spectroradiometric measures (Equation 6). The black line is our model's adjustment (Equations 8). Errors bars were derived from the StdDev of the averaged pixel regions at the centre of each square and the estimated 5% error of the measuring device.

Camera Model

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