What is the space of spectral sensitivity functions for digital color cameras?

Jiang, Jun; Liu, Dengyu; Gu, Jun; Süsstrunk, Sabine

doi:10.1109/wacv.2013.6475015

Cited by 268 publications

(230 citation statements)

References 16 publications

Supporting

Mentioning

227

Contrasting

Unclassified

Order By: Relevance

“…So, it is more practical to estimate-through statistical argument-the spectral sensitivities of a camera given, for example, the RGB response to known spectral stimuli. The need for spectral sensitivity estimation is increased because cameras made by the same manufacturer can have significantly different spectral sensitivities [6].…”

Section: Introductionmentioning

confidence: 99%

“…Novelly, we evaluate these methods with respect to the ground truth spectral sensitivities (e.g., using the same RGB data of the Macbeth ColorChecker [16,17] viewed under D65 that was used to validate our spectral measurements). Tested methods are Tikhonov regularization [18,19], Tikhonov based on derivatives [20], quadratic programming [21], and simple linear regression where the spectral sensitivities are assumed to lie in the basis of a linear model of small dimension [6,22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reference data set for camera spectral sensitivity estimation

et al. 2015

View full text Add to dashboard Cite

In this article, we describe a spectral sensitivity measurement procedure at the National Physical Laboratory, London, with the aim of obtaining ground truth spectral sensitivity functions for Nikon D5100 and Sigma SD1 Merill cameras. The novelty of our data is that the potential measurement errors are estimated at each wavelength. We determine how well the measured spectral sensitivity functions represent the actual camera sensitivity functions (as a function of wavelength). The second contribution of this paper is to test the performance of various leading sensor estimation techniques implemented from the literature using measured and synthetic data and also evaluate them based on ground truth data for the two cameras. We conclude that the estimation techniques tested are not sufficiently accurate when compared with our measured ground truth data and that there remains significant scope to improve estimation algorithms for spectral estimation. To help in this endeavor, we will make all our data available online for the community.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reference data set for camera spectral sensitivity estimation

et al. 2015

View full text Add to dashboard Cite

show abstract

“…This RGB calculation enables at least a qualitative comparison of the spectrometer measurements with the photograph image analysis results. To obtain the DoLP and AoLP for the RGB color bands, the Stokes vector for each band was calculated by summing the measured intensity weighted by the spectral sensitivity of the Canon D60 camera (Jiang et al, 2013) to red, green, or blue light, respectively, over the wavelengths (λ) of the respective band (see the section Polarization Photograph Analysis Method below). For wavelengths to which the camera is more sensitive, the spectrophotometer intensities are up-weighted accordingly, while for wavelengths at which the camera is less sensitive, the intensities are down-weighted accordingly.…”

Section: Spectrophotometer Methodsmentioning

confidence: 99%

Linear Polarization Characteristics Within the Rosh HaNikra Mid-Littoral Cave, Israel

et al. 2018

View full text Add to dashboard Cite

Light polarization characteristics, i. e., degree of linear polarization (DoLP) and angle of linear polarization (AoLP), were documented in the depth of the littoral cave system of Rosh HaNikra on the northern Mediterranean shore of Israel (33 • 5 ′ 35.24 ′′ N, 35 • 6 ′ 17.16 ′′ E), based on light intensity sampled through polarizing filters at different hours of the day on different days of the year. This is the first study to investigate the state of light polarization in such a unique habitat in which photosynthetic organisms, such as cyanobacteria, microalgae, and macroalgae thrive. Such organisms play an essential ecological role as the energy base for the cave's fauna. Using these two methods, we found unique winter polarization characteristics within the cave, including high values of DoLP in the morning and at noon, reaching 50%, and nearly constant AoLP throughout the day. Given the low levels of light intensity that typically exist within the cave in the winter months, the relatively high DoLP and the nearly constant AoLP throughout the day may play a significant role in improving the ability of photosynthetic organisms within the cave to harvest light by orienting their light-harvesting receptors with respect to the AoLP. Using the polarization photograph analysis method, we were able to determine the polarization characteristics originating from the sky, reflection off of (including refraction into followed by refraction out of) the far sea surface, and reflection off of the cave wall separately. The maximum DoLP values originating from the sky, far ocean, and cave walls were found to be 27, 50, and 35%, respectively. The lowest daily variation in AoLP was that of light reflecting off the cave walls. The present study lays the foundation for any subsequent study of the role of light polarization in the distribution of the algal flora on the cave walls in and out of the water in the Rosh HaNikra cave and in sea caves in general.

show abstract

“…There are many methods to estimate the sensor sensitivity M for a given camera [5] [6]. However, it is not an easy task to measure the scene illuminant every time along with the image acquisition.…”

Section: Spectral Adaptation Transformmentioning

confidence: 99%

Multispectral Constancy Based on Spectral Adaptation Transform

2017

View full text Add to dashboard Cite

Abstract. The spectral reflectance of an object surface provides valuable information about its characteristics. Reflectance reconstruction from multispectral images is based on certain assumptions. One of these assumptions is that the same illumination is used for system calibration and image acquisition. We propose the novel concept of multispectral constancy, achieved through a spectral adaptation transform, which transforms the sensor data acquired under an unknown illumination to a generic illuminant-independent space. The proposed concept and methods are inspired from the field of computational color constancy. Spectral reflectance is then estimated by using a generic linear calibration. Results of reflectance reconstruction using the proposed concept show that it is efficient, but highly sensitive to the accuracy of illuminant estimation.

show abstract

What is the space of spectral sensitivity functions for digital color cameras?

Cited by 268 publications

References 16 publications

Reference data set for camera spectral sensitivity estimation

Reference data set for camera spectral sensitivity estimation

Linear Polarization Characteristics Within the Rosh HaNikra Mid-Littoral Cave, Israel

Multispectral Constancy Based on Spectral Adaptation Transform

Contact Info

Product

Resources

About