I have 2D thermal image data. How to extract the features such as standard deviation, mean, entropy, skewness, kurtosis, mean absolute deviation from thermal image data?
Dear Danishtah Quamar,
As your question as formulated is very open (it is not clear whether the question is more specifically about mathematical formulas, software solutions, data analysis methodology, or anything else...), I propose to answer you by addressing these three different aspects.
About mathematical formulas, refer to :
- https://www.mdpi.com/2076-3417/10/18/6493/s1
- GNU Octave, Descriptive Statistics - https://docs.octave.org/latest/Descriptive-Statistics.html
- Armi et al., "TEXTURE IMAGE ANALYSIS AND TEXTURE CLASSIFICATION METHODS - A REVIEW", 2019 - https://arxiv.org/ftp/arxiv/papers/1904/1904.06554.pdf
About data analysis methodology, refer to:
- Armi et al., "TEXTURE IMAGE ANALYSIS AND TEXTURE CLASSIFICATION METHODS - A REVIEW", 2019 - https://arxiv.org/ftp/arxiv/papers/1904/1904.06554.pdf
- de Siqueira et al., "Multi-scale gray level co-occurrence matrices for texture description", 2013 - http://www.ssig.dcc.ufmg.br/wp-content/uploads/2014/09/2013-Multi-Scale-Gray-Level-Co-Occurrence-Matrices-for-Texture-Description.pdf
About software tools, refer to :
- Image Processing Toolbox by MathWorks - https://uk.mathworks.com/help/images/index.html?s_tid=CRUX_lftnav
- GNU Octave, Descriptive Statistics - https://docs.octave.org/latest/Descriptive-Statistics.html
Hoping it will be helpful.
Regards
I have the approximation and detailed coefficients obtained from the MATLAB software. Now I have to plot graphs between the STD vs Skew, STD vs Kurtosis, STD vs Entropy, and STD vs MAD at every level. How should I have to proceed?
I am attaching the results of MATLAB in this.
You can use statistical tool or use codes in Python. It will be helpful for you.
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