Improving light efficiency in multispectral imaging via complementary notch filters

Panther, Theresa; Schambach, Maximilian; Heizmann, Michael

doi:10.1117/12.2592411

Cited by 1 publication

(2 citation statements)

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“…where λ i = λ 0 + ib is the central wavelength of the ith notch filter. The ideal bandwidth of the optical filter [30] is given by b = (λ 1 − λ 0 )/N . Given the quantum efficiency Q(λ ) of a camera and the original amount of light entering it S(λ ), the light intensity of the corresponding wavelength on a single pixel using either a bandpass or a notch filter can be calculated using (4) and (5), respectively…”

Section: B Light Efficiency Analysismentioning

confidence: 99%

“…Furthermore, compared to spectral imaging systems based on bandpass filters, those implementing notch filters can achieve higher light pass efficiency and provide richer spectral information. Preliminary research results demonstrate that, in some scenarios, notch filters can achieve higher signal-to-noise ratios (SNRs) compared to bandpass filters [30]. Additionally, the system's performance is enhanced when using a notch filter for spectral [24] and night-vision imaging [31].…”

Section: Introductionmentioning

confidence: 99%

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High-Efficiency Multispectral-Polarization Imaging System Using Polarization Camera Array With Notch Filters

Huang,

Cao,

Lin

et al. 2023

IEEE Trans. Instrum. Meas.

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Incident light captured by an optical imaging system engenders multidimensional high-level optical information, such as spatial resolution, light intensity, spectrum, and polarization. However, panchromatic image sensors can only capture spatial and light intensity information. This article presents a novel multispectral-polarization imaging approach that overcomes the limitations related to low light flux and slow imaging speed found in multispectral-polarization techniques based on bandpass filters. By utilizing notch filters and a camera array and integrating computational imaging algorithms, this method achieves high temporal, spatial, and spectral resolution in polarization imaging for the first time. The spatial, light intensity, spectral, and polarization information of the target scene can be obtained synchronously while guaranteeing high light efficiency performance of the system. To obtain high spectral resolution polarization images, a K-times singular value decomposition (K-SVD) algorithm is used to extract the feature dictionary of the hyperspectral dimension. Then, a compressive sensing-based algorithm is applied to conduct spectral super-resolution. The principle of compressive sensing is combined with prior sparsity and smoothness information to perform spectral super-resolution. The performance of the proposed multispectral-polarization imaging system and the effectiveness of the proposed method were verified using a public multispectral dataset and field experiments. The experimental results confirm that the proposed technology can obtain high-quality spatial resolution, light intensity, spectral, and polarization data of the target scene in a single shot. The algorithm can reconstruct 16 spectral band images from four captured spectral images while adequately preserving the polarization information of the target scene in the calculated spectral imaging results.

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Section: B Light Efficiency Analysismentioning

confidence: 99%