Multispectral imaging has led to significant advances in various fields, including environmental monitoring, astronomy, agricultural sciences, biomedicine, medical diagnostics, and food quality control. The most widespread and rudimentary form of spectral imaging device is the color camera that collects information from the red (R), green (G) and blue (B) color channels.
The traditional design of RGB color cameras relies on spectral filters located spatially on a periodically repeating array of 2 × 2 pixels, with each subpixel containing an absorbing spectral filter that transmits one of the red, green, or blue channels while blocking the others.
Although widely used in various imaging applications, increasing the number of such absorbance filter arrays to collect richer spectral information from several distinct color ranges presents various challenges due to their low power efficiency, high spectral talk, and poor color representation quality.
UCLA researchers recently introduced a snapshot multispectral imager that uses a refractive optical grid, rather than absorptive filters, to acquire 16 unique spectral bands that repeat periodically in the field of view of the resulting image to form a virtual multispectral pixel array. This network-based multispectral imager is optimized using deep learning to spatially separate the input spectral channels on distinct pixels in the output image plane, and acts as a virtual spectral filter array that preserves the spatial information of the input scene or objects, resulting in image cube acquisition without redo algorithms. Image build.
Therefore, this multispectral scattering imaging network can transform a monochromatic image sensor into a snapshot multispectral imaging device without conventional spectral filters or digital algorithms.
Posted in Light: science and applications, it has been reported that the diffraction-based grid-based multispectral imaging framework provides high spatial imaging quality and high spectral signal contrast. The authors’ research shows that about 79% average transmission efficiency can be achieved over distinct bands without significantly compromising the system’s spatial imaging performance and spectral signal contrast.
Deniz Mengu et al., Multispectral imaging snapshot using a diffraction optical grid, Light: science and applications (2023). DOI: 10.1038/s41377-023-01135-0
the quote: Snapshot of Multispectral Imaging Using a Refractive Optical Grid (2023, April 6) Retrieved April 6, 2023 from https://phys.org/news/2023-04-snapshot-multispectral-imaging-diffractive-optical.html
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