Gray-Level Co-occurrence Matrix (GLCM) Implementation and Feature Extraction

Currently, I am working on a research paper that utilizes Gray-Level Co-occurrence Matrix (GLCM) analysis. After extensive searching without finding satisfactory implementations, I developed my own GLCM solution. While not flawless, it is fully functional and has been practically implemented. The codebase includes GLCM generation and calculation of multiple texture features using statistical algorithms. The implemented features are: f1 (Angular Second Moment - measures textural uniformity), f2 (Contrast - evaluates local intensity variations), f3 (Correlation - assesses linear dependencies between pixels), f5 (Inverse Difference Moment - quantifies local homogeneity), f6 (Sum Average - calculates mean of pixel sum probabilities), f7 (Sum Variance - measures dispersion of sum probabilities), f9 (Difference Average - computes mean of pixel difference probabilities), and f10 (Difference Variance - evaluates dispersion of difference probabilities). The implementation involves matrix operations and probability distribution calculations for texture analysis. I welcome any suggestions or feedback to improve this work and would greatly appreciate your valuable insights for further enhancement.