Iturrino García, Carlos

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    Acquiring multispectral information using computer tomography imaging spectrometer based algorithms
    (2019-10-07) Iturrino García, Carlos; Sierra, Heidy; College of Engineering; Arzuaga, Emmanuel; Rodríguez-Solís, Rafael A.; Department of Electrical and Computer Engineering; Morales-Vélez, Alesandra C.
    Spectral imaging has been used by scientists to acquire information across the electromagnetic spectrum for remote sensing applications. Most of the spectral systems are based on scanning methods that rely mainly on optomechanical components to acquire images from large areas. Usually, these configurations tend to be heavy and large in size limiting their use for low altitude imaging or their integration to commercial unmanned aerial vehicles (UAV). Small and compact spectral systems are available and allow to collect spectral images within a limited spectral range reducing their use to specific applications. Computed tomographic imaging spectrometer (CTIS) based approaches allow to recover spectral information by projecting the light to a single plane with the use of diffractive optical components and capturing the projected light in a single camera image. A spectral cube of images is then recovered by using reconstruction algorithms to invert the projection. This offers the ability of implementing a spectral system in a commercial camera.In this thesis a CTIS spectral imaging system is designed and characterized for acquiring low altitude spectral images. A customized convolutional algorithm to reconstruct a spectral cube of images is proposed and evaluated with respect to Expectation Maximization (EM) , QR Decomposition and Singular Value Decomposition (SVD) reconstruction algorithms. A detailed design analysis, characterization and calibration of a CTIS system prototype for a GoPro camera is performed. Experiments in the laboratory by using a mercury-argon lamp and a linear regression model provided an spectral range of 300 nm to 600 nm with a wavelength increment of 41.67 nm. The spatial resolution and measurement of the field of view is measured as function of the distance from the sensor to the imaged object. For an object located at 1 m from the CTIS system the field of view measures 132.95 cm2 of area. Experiments in the field are conducted for homogenous and heterogenous objects to evaluate the performance of the proposed convolution reconstruction algorithm. Images are also captured with a hyperspectral camera for validation. The results show that the proposed algorithm performs the reconstruction of a spectral cube with a lowest MSE of 0.038. The data recovery times of the convolutional reconstruction algorithm varies between 40 seconds to 1 minute while the traditional reconstruction algorithms times are around ˜20 minutes.