A plug-and-play Hyperspectral Imaging Sensor using low-cost equipment

Salazar-Vazquez, Jairo; Méndez-Vázquez, Andres

doi:10.1016/j.ohx.2019.e00087

Cited by 31 publications

(34 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From a monetary point of view, the used system costs less than 2000 euros, of which the machine vision camera costs roughly 1000 euros. Using cheaper camera and diffraction grating can bring the total price down to few hundred euros [ 8 ]. Recent development in 3D-printing imaging quality lenses [ 16 ] may lower the cost further in the future.…”

Section: Methodsmentioning

confidence: 99%

“…Commercial hyperspectral imagers (HSIs) are expensive, which restricts their usage for low-budget operators, such as individual researchers or landowners, as even the cheapest HSIs cost tens of thousands of euros [ 7 , 8 ]. Commercial HSIs are also heavy and bulky, which introduces additional requirements for drones utilized in UAV campaigns [ 8 ]. Several cheap HSIs have been introduced in the literature: some are made lightweight for UAV operations [ 8 , 9 ], while others target laboratory usage [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…Commercial HSIs are also heavy and bulky, which introduces additional requirements for drones utilized in UAV campaigns [ 8 ]. Several cheap HSIs have been introduced in the literature: some are made lightweight for UAV operations [ 8 , 9 ], while others target laboratory usage [ 7 ]. While several of these HSIs can be manufactured in do-it-yourself manner, calibration and aberration correction methods usually require access to an optical laboratory.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Do-It-Yourself Hyperspectral Imager Brought to Practice with Open-Source Python

Riihiaho¹,

Eskelinen²,

Pölönen³

2021

Sensors

View full text Add to dashboard Cite

Commercial hyperspectral imagers (HSIs) are expensive and thus unobtainable for large audiences or research groups with low funding. In this study, we used an existing do-it-yourself push-broom HSI design for which we provide software to correct for spectral smile aberration without using an optical laboratory. The software also corrects an aberration which we call tilt. The tilt is specific for the particular imager design used, but correcting it may be beneficial for other similar devices. The tilt and spectral smile were reduced to zero in terms of used metrics. The software artifact is available as an open-source Github repository. We also present improved casing for the imager design, and, for those readers interested in building their own HSI, we provide print-ready and modifiable versions of the 3D-models required in manufacturing the imager. To our best knowledge, solving the spectral smile correction problem without an optical laboratory has not been previously reported. This study re-solved the problem with simpler and cheaper tools than those commonly utilized. We hope that this study will promote easier access to hyperspectral imaging for all audiences regardless of their financial status and availability of an optical laboratory.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Do-It-Yourself Hyperspectral Imager Brought to Practice with Open-Source Python

Riihiaho¹,

Eskelinen²,

Pölönen³

2021

Sensors

View full text Add to dashboard Cite

show abstract

“…However, drone-based spectroscopy provides the opportunity to extend the coverage, providing a tool for rapid data collection. While other research has documented the potential for using small and lightweight imaging spectrometers on drone platforms (e.g., [21], little work has been done to test the extent to which the more affordable pointbased spectrometers can also capture categorical and continuous variable information about the benthos and water column.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Potential of Remotely-Sensed Drone Spectroscopy to Determine Live Coral Cover on Heron Reef

Cornet

Joyce

2021

Drones

View full text Add to dashboard Cite

Coral reefs, as biologically diverse ecosystems, hold significant ecological and economic value. With increased threats imposed on them, it is increasingly important to monitor reef health by developing accessible methods to quantify coral cover. Discriminating between substrate types has previously been achieved with in situ spectroscopy but has not been tested using drones. In this study, we test the ability of using point-based drone spectroscopy to determine substrate cover through spectral unmixing on a portion of Heron Reef, Australia. A spectral mixture analysis was conducted to separate the components contributing to spectral signatures obtained across the reef. The pure spectra used to unmix measured data include live coral, algae, sand, and rock, obtained from a public spectral library. These were able to account for over 82% of the spectral mixing captured in each spectroscopy measurement, highlighting the benefits of using a public database. The unmixing results were then compared to a categorical classification on an overlapping mosaicked drone image but yielded inconclusive results due to challenges in co-registration. This study uniquely showcases the potential of using commercial-grade drones and point spectroscopy in mapping complex environments. This can pave the way for future research, by increasing access to repeatable, effective, and affordable technology.

show abstract

“…Applications of these sensors have included agricultural vegetation modelling [ 4 , 5 ]; algal bloom investigation [ 6 ] and even deep space applications [ 7 ] as well as the possibility of carrying out remote geological surveys [ 8 ]. Multiple technologies have been devised and built to support these applications, including liquid crystal tunable filters [ 9 ], tunable Fabry–Perot filters [ 10 ] and diffractive optics [ 11 , 12 ]. Diffractive pushbroom hyperspectral sensors have found utility in low-cost research applications [ 11 , 12 ] and do not require electronically driven filters.…”

Section: Introductionmentioning

confidence: 99%

Appraisal of Low-Cost Pushbroom Hyper-Spectral Sensor Systems for Material Classification in Reflectance

Hobbs

Lambert

Ryan³

et al. 2021

Sensors

View full text Add to dashboard Cite

Near infrared (NIR) remote sensing has applications in vegetation analysis as well as geological investigations. For extra-terrestrial applications, this is particularly relevant to Moon, Mars and asteroid exploration, where minerals exhibiting spectral phenomenology between 600 and 800 nm have been identified. Recent progress in the availability of processors and sensors has created the possibility of development of low-cost instruments able to return useful scientific results. In this work, two Raspberry Pi camera types and a panchromatic astronomy camera were trialed within a pushbroom sensor to determine their utility in measuring and processing the spectrum in reflectance. Algorithmic classification of all 15 test materials exhibiting spectral phenomenology between 600 and 800 nm was easily performed. Calibration against a spectrometer considers the effects of the sensor, inherent image processing pipeline and compression. It was found that even the color Raspberry Pi cameras that are popular with STEM applications were able to record and distinguish between most minerals and, contrary to expectations, exploited the infra-red secondary transmissions in the Bayer filter to gain a wider spectral range. Such a camera without a Bayer filter can markedly improve spectral sensitivity but may not be necessary.

show abstract

A plug-and-play Hyperspectral Imaging Sensor using low-cost equipment

Cited by 31 publications

References 16 publications

A Do-It-Yourself Hyperspectral Imager Brought to Practice with Open-Source Python

A Do-It-Yourself Hyperspectral Imager Brought to Practice with Open-Source Python

Assessing the Potential of Remotely-Sensed Drone Spectroscopy to Determine Live Coral Cover on Heron Reef

Appraisal of Low-Cost Pushbroom Hyper-Spectral Sensor Systems for Material Classification in Reflectance

Contact Info

Product

Resources

About