The double pass imaging method is used to obtain the point spread function of a patient’s eye; however it suffers from speckle formation. Here we present a comparison of speckle formation in double pass imaging using three different semiconductor-based light sources.
This paper shows the simulations of the usage of a LED cluster as the illumination source for a multispectral imaging
system covering the range of wavelengths from 350 to 1650 nm. The system can be described as being composed of two
modules determined by the spectral range of the imaging sensors responses, one of them covering the range from 350-
950nm (CCD camera) and the other one covering the wavelengths from 900-1650nm (InGaAs camera). A well known
method of reflectance estimation, the pseudo-inverse method, jointly with the experimentally measured data of the
spectral responses of the cameras and the spectral emission of the LED elements are used for the simulations. The
performance of the system for spectral estimation under ideal conditions and realistic noise influence is evaluated
through different spectral and colorimetric metrics like the GFC, RMS error and CIEDE2000 color difference formula.
The results show that is expectable a rather good performance of the real setup. However, they also reveal a difference in
the performances of the modules. The second module has poorer performance due to the less narrow spectral emission
and less number of LED elements that covers the near-infrared spectral range.
This work is focused on the study and comparison of the performance for color measurements of different systems based on optoelectronic imaging sensors. We used two different configurations of the imaging system, one with three acquisition channels and the other with more spectral bands, in order to measure the color associated to each pixel of the captured scene. We applied different methodologies to obtain the XYZ tristumulus values from the measured digital signals. The different techniques included an absolute spectral and colorimetric characterization of the system and also direct transformations between both sets, which used several mathematical fittings such as the pseudo-inverse technique, a non-linear estimation method and the principal component analysis. The proposed configurations were experimentally tested imaging the patches of the Gretagmacbeth ColorChecker DC and Color Rendition charts placed in
a light booth, and measuring the corresponding colors. The results obtained showed that optoelectronic imaging systems can be used in order to perform rather accurate color measurements with high spatial resolution. Specifically, the best results in terms of CIELab color differences were achieved by using a multispectral configuration of the imaging system with seven spectral bands and directly transforming the digital signals into XYZ tristimulus values by means of the pseudo-inverse technique.
The near infrared spectral region (NIR) is useful in many applications. These include agriculture, the food and chemical industry, and textile and medical applications. In this region, spectral reflectance measurements are currently made with conventional spectrophotometers. These instruments are expensive since they use a diffraction grating to obtain monochromatic light. In this work, we present a multispectral imaging based technique for obtaining the reflectance spectra of samples in the NIR region (800 - 1000 nm), using a small number of measurements taken through different channels of a conventional CCD camera. We used methods based on the Wiener estimation, non-linear methods and principal component analysis (PCA) to reconstruct the spectral reflectance. We also analyzed, by numerical simulation, the number and shape of the filters that need to be used in order to obtain good spectral reconstructions. We obtained the reflectance spectra of a set of 30 spectral curves using a minimum of 2 and a maximum of 6 filters under the influence of two different halogen lamps with color temperatures Tc<sub>1</sub> = 2852K and Tc<sub>2</sub> = 3371K. The results obtained show that using between three and five filters with a large spectral bandwidth (FWHM = 60 nm), the reconstructed spectral reflectance of the samples was very similar to that of the original spectrum. The small amount of errors in the spectral reconstruction shows the potential of this method for reconstructing spectral reflectances in the NIR range.
An algorithm is proposed for the spectral and colorimetric characterization of digital still cameras (DSC) which allows to use them as tele-colorimeters with CIE-XYZ color output, in cd/m<sup>2</sup>. The spectral characterization consists of the calculation of the color-matching functions from the previously measured spectral sensitivities. The colorimetric characterization consists of transforming the RGB digital data into absolute tristimulus values CIE-XYZ (in cd/m<sup>2</sup>) under variable and unknown spectroradiometric conditions. Thus, at the first stage, a gray balance has been applied over the RGB digital data to convert them into RGB relative colorimetric values. At a second stage, an algorithm of luminance adaptation vs. lens aperture has been inserted in the basic colorimetric profile. Capturing the ColorChecker chart under different light sources, the DSC color analysis accuracy indexes, both in a raw state and with the corrections from a linear model of color correction, have been evaluated using the Pointer'86 color reproduction index with the unrelated Hunt'91 color appearance model. The results indicate that our digital image capture device, in raw performance, lightens and desaturates the colors.