Spectral Cross-Correlation Map

Features:

• Enables to draw a seed and cross-correlate with the rest of the image.

• Identifies the area of the highest/lowest cross-correlation.

• Quantifies the area correlated with the seed.

Steps:

1.       Press the button Spectral Mathematics on the Main Interface under SPECTRAL ANALYSIS.

2.       Select Spectral Correlation Map from a dropdown menu.

3.       Select 1st spectrum.

4.       Draw a region of interest that can be used as a reference point (seed) and visualize the mean spectrum.

5.       Click Generate to open another window Spectral Correlation Map.

6.       Visualize and quantify a Spectral Cross-Correlation Map.

Higher cross-correlation corresponds to a closer match between the seed and each pixel in the image. Use a slider on the histogram to visualize the images with the highest or lowest correlation. The area of the matched cross-correlation (high cross-correlation) is shown in the title.

The Reset button can be used to revert the image to the original.

Additional Information:

The toolbox is based on a spectral cross-correlation algorithm that computes the p-values for Pearson's correlation using a Student's t distribution for a transformation of the correlation.

Values of the correlation coefficient can range from –1 to +1. A value of –1 indicates a perfect negative correlation, while a value of +1 indicates a perfect positive correlation. A value of 0 indicates no correlation between the seed and the pixel.

References:

Gibbons, J.D. Nonparametric Statistical Inference. 2nd ed. M. Dekker, 1985.

Hollander, M., and D.A. Wolfe. Nonparametric Statistical Methods. Wiley, 1973.