Spectral sensitivity measurement with camSPECS

camSPECS enables spectral sensitivity measurement more effectively by mounting all interference filters on a single “test chart.” The newest version uses new high-quality interference filters. The light source is designed to ensure equal power output across the interference filters and not exceed the camera's dynamic range. Neutral-density filters on the front plate are used to compensate for potential illumination non-uniformities. The camSPECS hardware consists of a metal housing with a stabilized power supply for the halogen light source. The 39 interference filters, mounted on the front plate, provide monochromatic light from 380 nm to 760 nm.

camSPECS measures spectral sensitivity more effectively by mounting all interference filters on a single “test chart.” The newest version uses new high-quality interference filters.

The light source is designed to ensure equal power output across the interference filters and not exceed the camera's dynamic range. Neutral-density filters on the front plate are used to compensate for potential illumination non-uniformities.

The camSPECS hardware consists of a metal housing with a stabilized power supply for the halogen light source. The 39 interference filters, mounted on the front plate, provide monochromatic light from 380 nm to 760 nm.

The spectral sensitivity of a camera is interesting to examine, but the real benefit is using it to calculate the optimal color correction matrix for the camera. The camSPECS software includes a module for calculating such matrices. Three algorithms are implemented: a least-squares linear regression, a white-point-preserving least-squares regression, and the CIECAM16 model. The required input data are the camera spectral response, the illumination spectral distribution, and the spectral training data.

The required training data can be either the provided ColorChecker spectra or measured spectra of natural objects. Image Engineering provides access to a large database of in situ spectral radiance data. White balancing can be incorporated into the matrix calculation as a separate option.

Once the camera spectral sensitivities are determined, it is possible to build optimal color transforms to convert camera values to colorimetric values. By including reference illumination and standard chart data (or newly available, specially measured in situ training data representative of real scenes), color transforms are built that optimize color appearance differences using CIECAM16. Various methods and transform types are supported, including colorimetric matrices, white-point-preserving transforms, and ICC profiles, with more being added continuously.