visualization of hyperspectral images
DESCRIPTION
VISUALIZATION OF HYPERSPECTRAL IMAGES. ROBERTO BONCE & MINDY SCHOCKLING iMagine REU Montclair State University. Presentation Overview. Hyperspectral Images Wavelet Transform Denoising MATLAB code and results Future Work References. What are hyperspectral images?. - PowerPoint PPT PresentationTRANSCRIPT
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VISUALIZATION OF HYPERSPECTRAL IMAGES
ROBERTO BONCE & MINDY SCHOCKLINGiMagine REU Montclair State University
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Presentation Overview
Hyperspectral Images Wavelet Transform Denoising MATLAB code and results Future Work References
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What are hyperspectral images?
Most images contain only data in the color spectrum
Hyperspectral images contain data from several, continuous wavelengths
Our camera records data from 400nm to 900nm
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Hyperspectral cont.
Hyperspectral images can be thought of as being stacked on top of each other, creating an image cube
This creates a pixel vector, the vector can be used to distinguish one material from another
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Pictures
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Wavelets: “small waves”
Decay as distance from the center increases
Have some sense of periodicity
Can perform local analysis unlike Fourier
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Wavelet Analysis and Reconstruction
Original signal is sent through high and low pass filters
Approximation: low frequency, general shape Detail: high frequency, noise Reconstruction involves filtering and
upsampling
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Noisy Sine
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The Project
Analyzing hyperspectral signatures for image analysis can be very computationally expensive
An alternative approach is to select a subset of the images and apply a weighting scheme to generate a useful image
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Project Cont.
The plant to the right contains both real and artificial leaves
Goal: distinguish between real and artificial leaves
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Last Year (2007)
Focus bands were chosen Applied a weighting scheme
To give infrared data more importance because the visual data is too similar
An RGB composite image is created
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Last Year
Composite image to the right
They used the distance series
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Preliminary results
Tried weighting, wavelet transform, different focus bands.
Results were somewhat disappointing
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Procedure
Artificial leaves have a second peak in near-infrared region
By centering a focus band in this region, real and artificial leaves can be visualized
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Results
Original Image
(R:60, G:30, B:20)
Band-Shifted Image
(R:90, G:30, B:20)
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Future Work
Further explore the use of wavelets for denoising data
Continue to investigate various weighting schemes
Attempt to classify or distinguish between other materials besides leaves
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References:
http://www.microimages.com/getstart/pdf/hyprspec.pdf
Images from http://www.wikipedia.org/
MATLAB help