סמינר תואר שני - Hyperspectral Image Reconstruction Using Tunable MEMS Fabry-Perot Imager By: Hila Gabay
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You are invited to attend a lecture on Tuesday, March 28, 2023 15:00
Hyperspectral Image Reconstruction Using Tunable MEMS Fabry-Perot Imager
MSc. student under the supervision of Prof. David Mendlovic
Smartphones' proliferation of computational photography and optical capabilities have made them the default choice for most users. However, most affordable handheld devices can only capture visible and near-infrared light, limiting our perspective of the world.
Hyperspectral imaging divides the spectrum into many more bands, some beyond the visible range.
Hyperspectral imaging has numerous advantages in multiple fields; agriculture, astronomy, biomedical imaging, and geoscience. By combining conventional imaging and spectroscopy, this technique can simultaneously collect spatial and spectral information from an object, allowing for the identification of surface materials through their unique spectral signature.
Tunable MEMS Fabry-Perot interferometers (FPIs) are developed to address this issue, offering a compact device structure and the ability to capture a broad spectrum of light.
A complex imaging processing pipeline is required to maintain high resolution and image quality.
This thesis makes two contributions: firstly, an optimization process for multi-layer Fabry-Perot to determine the optical specifications of the hyperspectral system in terms of SNR and spectral resolution, and secondly, a post-processing pipeline for hyperspectral signal reconstruction to achieve optimal image quality and meet the system’s optical demands. Using MEMS technology with an off-the-shelf RGB sensor and an algorithmic pipeline, miniature and affordable handheld devices for hyperspectral imaging can be achieved.
By utilizing MEMS technology in combination with an RGB sensor readily available on the market and implementing an algorithmic pipeline, it is possible to create compact and cost-effective handheld devices capable of hyperspectral imaging.
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