Normalization

Features:

• Applies a normalization algorithm to the spectral axis of the dataset having all intensity values in the range between 0 and 1.

• This operation is global and will be retained for all other functions and treatments.

Steps:

Select Filtering and Enhancement → Normalization → Normalization [0 1]. Visualize the normalized image. The colorbar values are between 0 and 1. This rescaled image can be returned to the original by using Filtering and Enhancement → Remove all Filters and Enhancements or Reset button.

Note: PAVIA is used as an example.

Features:

Applies a normalization algorithm to the spectral axis of the dataset having all intensity values in the range of the Z-score. Z-score describes the deviation from the mean in the number of standard deviations. The Z-score is positive when the sample is above the mean and negative when below.

This operation is global and will be retained for all other functions and treatments.

Steps:

1.       Select Filtering and Enhancement → Normalization → Z-score Normalization 

2.       After completion, click OK and visualize the normalized image. The colorbar values are within the Z-score.

3.     This rescaled image can be returned to the original by using Filtering and Enhancement  Remove all Filters and Enhancements or Reset button.

Tip: Use histogram to visualize parts of the image with positive or negative Z score values.