Investigation of a compressive line sensing hyperspectral imaging sensor

Bing Ouyang; Michael Twardowski; Yanjun Li; Fraser Dalgleish

doi:10.1117/12.2309937

24 May 2018 Investigation of a compressive line sensing hyperspectral imaging sensor

Bing Ouyang, Michael Twardowski, Yanjun Li, Fraser Dalgleish

Proceedings Volume 10677, Unconventional Optical Imaging; 106773Q (2018) https://doi.org/10.1117/12.2309937
Event: SPIE Photonics Europe, 2018, Strasbourg, France

Abstract

Passive hyperspectral imaging (HSI) sensors are essential in many space-borne surveillance missions because rich spectral information can improve the ability to analyze and classify oceanic and terrestrial parameters and objects/areas of interest. A significant technical challenge is that the amount of raw data acquired by these sensors will begin to exceed the data transmission bandwidths between the spacecraft and the ground station using classical approaches such as imaging onto a detector array. In this paper, the Compressive Line Sensing (CLS) imaging concept, originally developed for energy-efficient active laser imaging, is extended to the implementation of a hyperspectral imaging sensor. CLS HSI imaging is achieved using a digital micromirror device (DMD) spatial light modulator. A DMD generates a series of 2D binary sensing patterns from a codebook that can be used to encode cross-track spatial-spectral slices in a push-broom type imaging device. A high sensitivity single-element detector can then be used to acquire the target reflections from the DMD as the encoder output. The target image can be reconstructed using the encoder output and the encoding codebook. The proposed system architecture is presented. The initial simulation and experimental results comparing the proposed design with the state-of-the-art are discussed.

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Bing Ouyang, Michael Twardowski, Yanjun Li, and Fraser Dalgleish "Investigation of a compressive line sensing hyperspectral imaging sensor", Proc. SPIE 10677, Unconventional Optical Imaging, 106773Q (24 May 2018); https://doi.org/10.1117/12.2309937

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KEYWORDS

Sensors

Digital micromirror devices

Imaging systems

Principal component analysis

Hyperspectral imaging

Signal to noise ratio

Image compression

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