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HYPERSPECTRAL IMAGES USING COMPUTATIONAL ENGINEERING
HYPERSPECTRAL IMAGES USING COMPUTATIONAL ENGINEERING
FORMATION OF HYPERSPECTRAL IMAGES USING COMPUTATIONAL ENGINEERING
Images are quite often used for comparison to identify changes in an environment. The field of Computational Engineering is able to model and analyze such changes and for that, different types of images are considered.
The most common of these images is a three-layer RGB image which symbolizes the environmental condition viewed at Red wavelength, Green wavelength, and Blue wavelength all layered together on top of each other to form a single-color image.
Adding further layers at various wavelengths now exceeding the three layers, the image enters the multi-spectral and hyper-spectral image domain. As points of observation (wavelength) have increased, so have the details or information collected from the image.
To form such images, material conditions are required. Major recent works aim for a modeling, analysis, and prediction tool for generating IR signature with segmental analysis of various environments (water, vegetation, rocks, etc.) based on transient heat transfer, flow state, and material composition (e.g., density, specific heat, thermal conductivity).
To reduce errors of computation when compared with actual experimental results, experimental emissivity and reflectance are introduced for IR signature calculation.
www.wanttono.com/education/hyperspectral-images-using-com...
HYPERSPECTRAL IMAGES USING COMPUTATIONAL ENGINEERING
HYPERSPECTRAL IMAGES USING COMPUTATIONAL ENGINEERING
FORMATION OF HYPERSPECTRAL IMAGES USING COMPUTATIONAL ENGINEERING
Images are quite often used for comparison to identify changes in an environment. The field of Computational Engineering is able to model and analyze such changes and for that, different types of images are considered.
The most common of these images is a three-layer RGB image which symbolizes the environmental condition viewed at Red wavelength, Green wavelength, and Blue wavelength all layered together on top of each other to form a single-color image.
Adding further layers at various wavelengths now exceeding the three layers, the image enters the multi-spectral and hyper-spectral image domain. As points of observation (wavelength) have increased, so have the details or information collected from the image.
To form such images, material conditions are required. Major recent works aim for a modeling, analysis, and prediction tool for generating IR signature with segmental analysis of various environments (water, vegetation, rocks, etc.) based on transient heat transfer, flow state, and material composition (e.g., density, specific heat, thermal conductivity).
To reduce errors of computation when compared with actual experimental results, experimental emissivity and reflectance are introduced for IR signature calculation.
www.wanttono.com/education/hyperspectral-images-using-com...