Comparative Colorimetric Simulation and Evaluation of Digital Cameras Using Spectroscopy Data (original) (raw)

Testing and optimizing the spectral response of digital cameras

Imaging Science journal, 2005

A colorimetric analysis and design method for cameras is presented which enables a camera to be used as an imaging colorimeter, capable of capturing an accurate record of the Commission Internationale de l'Éclairage (CIE) coordinates of the imaged objects. The spectral response characteristics of some of the component observers in the 1964 CIE Standard Observer average are first analysed and compared. CIE colour coordinates are calculated using both the Standard Observer average and individual observer CMFs for each of 32 test colours. The personal coordinates for each observer are then linked to differences in their visual response CMFs at the spectral level. A colorimetric testing and optimization method for cameras is then reported, which allows the colour capture properties of imaging systems to be analysed, controlled and modified. The method is based on imaging spectrally defined colour charts and is used to demonstrate that even minor differences in the chosen RGB filter/sensor characteristics substantially affect the numeric accuracy of the colour-defining information in images. Colour imaging error is quantified and minimized, first by establishing the camera RGB to CIE XYZ relationship, and then by adjusting the spectral response of the sensors. Under controlled lighting and exposure conditions, the design method enables output pixel-colour definitions that are a close analogue of the measured CIE XYZ tristimulus values for the imaged surface colours.

Practical camera characterization for colour measurement

The Imaging Science Journal, 2001

This paper reviews the major issues involved in the use of digital cameras to derive the CIE X, Y and Z tristimulus values of objects in real scenes. Both practical and theoretical investigations have been carried out to gain experience in this specialized field of imaging that is finding application in, for example, machine vision, product quality assessment by panel observation and digital archiving of art objects. The practicalities of camera characterization described include: lighting-spectral power and uniformity; test target-choice and number of colours; camera signal processing-linear or gamma corrected; colour analysis-filter transmittance and infrared filtration; characterization method-linear or higher order; quality measure-CIELAB, CMC, CIE94 colour difference; quality statistic-mean, median, etc. The potential impact of these parameters is discussed by the use of a computer model and from practical experience. It is shown, as might be expected, that the choice of colour separation filtration is the most sensitive variable. If a 'colour' camera is used, then it needs to be carefully selected; a more adaptable choice, however, may be a monochrome camera with external filters. In addition, the illumination uniformity of the test target used for characterization is shown to be important: that it is never perfectly uniform must be considered in the characterization process. With careful selection of system components, a median value of less than 1.0 CIELAB colour difference can be obtained between independently measured colorimetry and that calculated from the camera output.

Characterization of a digital camera as an absolute tristimulus colorimeter

2003

An algorithm is proposed for the spectral and colorimetric characterization of digital still cameras (DSC) which allows them to be used as tele-colorimeters with CIE-XYZ color output, in cd/m 2 . The spectral characterization consists in the calculation of the color-matching functions from the previously measured spectral sensitivities. The colorimetric characterization consists in transforming the raw RGB digital data into absolute tristimulus values CIE-XYZ (in cd/m 2 ) under variable and unknown spectroradiometric conditions. Thus, in the first stage, a gray balance was applied over the raw RGB digital data to convert them into RGB relative colorimetric values. In the second stage, an algorithm of luminance adaptation versus lens aperture was inserted in the basic colorimetric profile. Capturing the ColorChecker chart under different light sources, and comparing the estimated XYZ data according to the developed color model in relation to the measured XYZ data (in cd/m 2 ) using a telespectroradiometer, we verified that the proposed characterization model may be broken down into two portions. Firstly, there is the basic colorimetric profile in combination with the new luminance adaptation algorithm. Secondly, there is the linear correction term due only to the mismatch of the color matching functions of the camera. Although the linear color correction term works relatively well, despite the imposed initial conditions (unknown spectral content of the scene), the separation of the proposed characterization model into two portions (raw and corrected performance) would allow the future comparison of various commercial cameras.

A strategy toward spectral and colorimetric color reproduction using ordinary digital cameras

Color Research & Application, 2018

In this work, a methodology is introduced to use ordinary digital RGB cameras for the purpose of spectral and colorimetric color reproduction. First, it is attempted to recover the spectral reflectance from RGB camera response using different approaches, among which, it is shown that weighted nonlinear regression as performed better than other approaches. After analyzing the results, it is realized that although spectrally the results are satisfactory, there is still a significant colorimetric error left, that should be addressed. Therefore, in the second part of the article, different linear and nonlinear matrix transforms are used to change the RGB camera response to CIEXYZ tristimulus values under a specific condition. It is concluded that colorimetric error of the recovery can be reduced significantly when a separate path is used for colorimetric color reproduction.

Estimation of the device gamut of a digital camera in raw performance using optimal color-stimuli

Using a spectroradiometric model of capture for a digital camera based on the mathematical description of the empirical opto-electronic conversion spectral functions (OECSF), the capture of MacAdam or optimal spectra with fixed illumination level is simulated. This model of capture allows to change freely the f-number of the zoom-lens and/or the photosite integration time of the electronic shutter of the camera, regardless of the spectral composition of the stimulus. If we follow the procedure employed by MacAdam in 1935 working with the CIE-1931 XYZ standard observer, these color-stimuli are arranged in decreasing pyramidal form as the luminance factor increases for any chromaticity diagram (CIE-xy, UCS-u'v' or CIE-L*a*b*). These loci are often called MacAdam limits or Rösch color solid. On the other hand, transforming the simulated RGB digital output levels of the optimal colors to XYZ data through the raw colorimetric profile with luminance adaptation of our digital image capture device, the corresponding MacAdam loci for each luminance factor are smaller than those of the colorimetric standard observer. This systematic desaturation of the optimal color-stimuli shows that our color device, in raw performance, desaturates in general the real color-stimuli, so this result justifies the additional use in digital photography of color correction algorithms, more or less complex, in order to reach the colorimetric status of color reproduction.

Digital Camera Characterization for Color Measurements

The use of spectrophotometers for color measurements on printed substrates is widely spread among paper producers as well as within the printing industry. Spectrophotometer measurements are precise, but timeconsuming procedures and faster methods are desirable. Colorimetrically calibrated flatbed scanners have been proved to provide a fast and fairly accurate alternative to spectrophotometers. Moreover, the rapid development of digital cameras has made it possible to transfer successfully implemented methods for color calibration of flatbed scanners to a camera-based system.

Imaging colorimetry using a digital camera

In this work, we investigate the use of a digital camera for colorimetry. Our system consists of a measurement device and a corresponding calibration mapping. The goal is to design a system that will accurately assess the color of a sample. We develop two colorimetry systems by applying model-based and regression-based techniques. For both systems, the measurement device is formed by a digital camera and a set of filters. The term multi-exposure refers to the multiple snapshots taken by the camera along with filters. The calibration mapping which consists of matrices then takes these filtered camera RGB outputs, and returns the CIE XYZ tristimulus values under several pre-selected illumination conditions. For the model-based system, a model for the measurement device is employed; and our objective is to find the optimal filters and the corresponding calibration sets that minimize a cost function which accounts for errors in L*a*b* space, system robustness, and filter smoothness. For the regression-based system, no modeling technique is applied to the measurement device. The objective is simply to find the optimal calibration matrices that minimize the total least squared errors of a given color set in CIE XYZ coordinates under several pre-selected illumination conditions. We apply both types of colorimetry systems to two specific tasks: general purpose measurement of color samples and colorimetry of human teeth. We present experimental results for both applications. Finally, in order to measure the parameters for these systems and evaluate their performance, we had to develop special instrumentation. We will briefly describe this effort as well.

Camera characterization for color research

Color Research & Application, 2002

We introduce a new method for estimating camera sensitivity functions from spectral power input and camera response data. We also show how the procedure can be extended to deal with camera non-linearities. Linearization is an important part of camera characterization and we argue that it is best to jointly fit the linearization and the sensor response functions. We compare our method with a number of others, both on synthetic data and for the characterization of a real camera. All data used in this study is available on-line at http://www.cs.sfu.ca/\~colour/data.

Concerning the calculation of the color gamut in a digital camera

Color Research & Application, 2006

Several methods to determine the color gamut of any digital camera are shown. Since an input device is additive, its color triangle was obtained from their spectral sensitivities and it was compared with the theoretical sensors of Ives-Abney-Yule and MacAdam. On the other hand, the RGB digital data of the optimal or MacAdam colors were simulated to transform them into XYZ data according to the colorimetric profile of the digital camera. From this, the MacAdam limits associated to the digital camera are compared with the corresponding ones of the CIE-1931 XYZ standard observer, resulting that our color device has much smaller MacAdam loci than those of the colorimetric standard observer. Taking this into account, we have estimated the reduction of discernible colors by the digital camera applying a chromatic discrimination model and a packing algorithm to obtain color discrimination ellipses. Calculating the relative decrement of distinguishable colors by the digital camera in comparison with the colorimetric standard observer at different luminance factors of the optimal colors, we have found that the camera distinguishes considerably fewer very dark than very light ones, but relatively much more colors with middle lightness (Y between 40 and 70, or L* between 69.5 and 87.0). This behavior is due to the short dynamic range of the digital camera response.