Titlebook: Hyperspectral Imaging Technology in Food and Agriculture; Bosoon Park,Renfu Lu Book 2015 Springer Science+Business Media New York 2015 Hyp

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Hyperspectral Image Processing Methodsage processing workflow for near-sensing applications includes normalization, correction, dimensionality reduction, spectral library building, and data processing. In this book chapter, recent advances in hyperspectral image processing algorithms and workflows for hyperspectral image processing are

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Real-Time Hyperspectral Imaging for Food Safetyne-scan hyperspectral imaging system for real-time multispectral imaging applications for the food industry is demonstrated. The real-time hyperspectral imaging system consists of a spectrograph, EMCCD camera, and real-time image processing software. The imaging system can be easily modified for oth

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AOTF Hyperspectral Imaging for Foodborne Pathogen Detection scattering signature from different bacterial species can be observed at the selected wavelengths. Since scattering peak intensity at various wavelengths depends on bacterial serotypes as well as species, statistical models can be developed to classify different foodborne bacteria. Herein, we intro

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emical interactions, thermal interactions (e.g., coagulation and vaporization), photoablation, plasma-induced ablation, and photodisruption. Two key phenomena used in tissue analyses are random interference patterns or speckle fields and the principles of fluorescence.

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