Designing Color Filters That Make Cameras More Colorimetric

Design of non-Gaussian multispectral shortwave infrared filters assessed by surface spectral reflectances on the ECOSTRESS library

This paper addresses the multispectral filter design problem for spectral ranges where a viewing subspace is not defined. The methodology of color filter design is extended to this case, which allows the optimization of custom filter transmittance that meets the physical constraints of available fabrication methods. Multispectral shortwave infrared filters are then designed for two scenarios: spectral reconstruction and false-color representation. The Monte Carlo method is used to verify the filter performance degradation due to deviations in fabrication. The results obtained indicate that the proposed method is useful for designing multispectral filters to be fabricated using generic processes without any additional constraints.

Wide-Angular Tolerance Optical Filter Design and Its Application to Green Pepper Segmentation

The optical filter is critical in many applications requiring wide-angle imaging perception. However, the transmission curve of the typical optical filter will change at an oblique incident angle due to the optical path of the incident light change. In this study, we propose a wide-angular tolerance optical filter design method based on the transfer matrix method and automatic differentiation. A novel optical merit function is proposed for simultaneous optimization at normal and oblique incidents. The simulation results demonstrate that such a wide-angular tolerance design can realize a similar transmittance curve at an oblique incident angle compared to a normal incident angle. Furthermore, how much improvement in a wide-angular optical filter design for oblique incident contributes to image segmentation remains unclear. Therefore, we evaluate several transmittance curves along with the U-Net structure for green pepper segmentation. Although our proposed method is not perfectly equal to the target design, it can achieve an average 50% smaller mean absolute error (MAE) than the original design at 20∘ oblique incident angle. In addition, the green pepper segmentation results show that wide-angular tolerance optical filter design improves the segmentation of the near-color object about 0.3% at 20∘ oblique incident angle compared to the previous design.

Matched illumination: using light modulation as a proxy for a color filter that makes a camera more colorimetric

In previous work, it was shown that a camera can theoretically be made more colorimetric-its RGBs become more linearly related to XYZ tristimuli-by placing a specially designed color filter in the optical path. While the prior art demonstrated the principle, the optimal color-correction filters were not actually manufactured. In this paper, we provide a novel way of creating the color filtering effect without making a physical filter: we modulate the spectrum of the light source by using a spectrally tunable lighting system to recast the prefiltering effect from a lighting perspective. According to our method, if we wish to measure color under a D65 light, we relight the scene with a modulated D65 spectrum where the light modulation mimics the effect of color prefiltering in the prior art. We call our optimally modulated light, the matched illumination. In the experiments, using synthetic and real measurements, we show that color measurement errors can be reduced by about 50% or more on simulated data and 25% or more on real images when the matched illumination is used.

A Mathematical Investigation into the Design of Prefilters That Make Cameras More Colorimetric

By placing a color filter in front of a camera we make new spectral sensitivities. The Luther-condition optimization solves for a color filter so that the camera’s filtered sensitivities are as close to being linearly related to the XYZ color matching functions (CMFs) as possible, that is, a filter is found that makes the camera more colorimetric. Arguably, the more general Vora-Value approach solves for the filter that best matches all possible target spectral sensitivity sets (e.g., any linear combination of the XYZ CMFs). A concern that we investigate here is that the filters found by the Luther and Vora-Value optimizations are different from one another. In this paper, we unify the Luther and Vora-Value approaches to prefilter design. We prove that if the target of the Luther-condition optimization is an orthonormal basis—a special linear combination of the XYZ CMFs which are orthogonal and are in unit length—the discovered Luther-filter is also the filter that maximizes the Vora-Value. A key advantage of using the Luther-condition formulation to maximize the Vora-Value is that it is both simpler to implement and converges to its optimal answer more quickly. Experiments validate our method.