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I have implemented GLCM Texture analysis on the Sentinel-1 SAR imagery. The imagery is high resolution. The parameters for the GLCM texture analysis are:

Window size: 5x5

Quantizer: Probablistic Quantizer

Quantization: 64 bit

Angle: 0 degree

Displacement: 1

The output is 10 different texture images. However the range of pixel values is not between 0 and 1. The range for every texture is between different min and max values. I believe this should be between 0 and 1 as it is a probabilistic analysis with GLCM that is being calculated for every pixel.

Am I missing a step?

Tonechas
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webapp
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1 Answers1

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I guess you are getting 10 different images because for each image pixel you are performing the following operations:

  • Define a neighbourhood of 5×5 centered at the considered pixel.
  • Compute the GLCM corresponding to displacement=1 and angle=0 of that neighbourhood.
  • Extract 10 features from the local GLCM.

This results in a stack of 10 images, one image for each feature extracted from the local GLCMs.

The problem is that Haralick features are not normalized to 1. Consider for example the standard definition of entropy:

Entropy

If you wish to obtain entropy value in the range [0, 1] you should divide the equation above by the maximum entropy (measured in bits), like this:

Normalized entropy

where N_g is the number of different grey levels.

This paper explains how to normalize contrast, correlation, energy, entropy and homogeneity features extracted from GLCM so that they have range [0, 1].

Tonechas
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  • So, this means even though it is a probabilistic analysis, the min and max value will not be between 0 and 1. In order to do so, I will have to divide each pixel value (probability) by the max pixel value present in the image. Am I right? – webapp Jul 16 '18 at 17:37
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    The GLCM is normalized so that the sum of their elements is 1. However, not all the Haralick features are normalized to the range 0-1. Concretely, the entropy of the GLCM can be greater than 1 (as shown in my answer). [This paper](https://www.sciencedirect.com/science/article/pii/S016786551400124X?via%3Dihub) explains how to normalize 5 Haralick features to have range [0, 1]. – Tonechas Jul 16 '18 at 17:47