VISUALIZATION OF HYPERSPECTRAL IMAGES

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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 Presentation

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VISUALIZATION OF HYPERSPECTRAL IMAGES

ROBERTO BONCE & MINDY SCHOCKLINGiMagine REU Montclair State University

Presentation Overview

Hyperspectral Images Wavelet Transform Denoising MATLAB code and results Future Work References

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

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

Pictures

Wavelets: “small waves”

Decay as distance from the center increases

Have some sense of periodicity

Can perform local analysis unlike Fourier

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

Noisy Sine

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

Project Cont.

The plant to the right contains both real and artificial leaves

Goal: distinguish between real and artificial leaves

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

Last Year

Composite image to the right

They used the distance series

Preliminary results

Tried weighting, wavelet transform, different focus bands.

Results were somewhat disappointing

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

Results

Original Image

(R:60, G:30, B:20)

Band-Shifted Image

(R:90, G:30, B:20)

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

References:

http://www.microimages.com/getstart/pdf/hyprspec.pdf

Images from http://www.wikipedia.org/

MATLAB help