Matlab Image Analysis: Exploration (mean spectra/images, false RGB, PCA) + Masking data + Pretreatments (SNV, Savitsky) + Clustering (k-means) + Classification (Compare calibration and test set) + Analyze wavelengths contribution to classification.

The project involves analyzing a set of hyperpectral images and
• exploring the data with mean spectra, mean images, false RGB images, PCA
• masking the images
• choosing and applying a relevant pretreatment (can be snv, smoothing, savitsky)
• clustering with k means and interpret
• classify the data between calibration and test set and analyze
• discuss wavelengths or wavelength impact in classification

needed are the code and some of the written analysis

Ideal Skills and Experience:
- Advanced proficiency in Matlab for image analysis
- Strong understanding of mean spectra/images exploration, false RGB, PCA, masking data, pretreatments (SNV, Savitsky), clustering (k-means), classification, and wavelength analysis
- Experience in working with large datasets and performing complex data analysis
- Knowledge of statistical analysis techniques and algorithms

If you have the necessary skills and experience in Matlab image analysis and can complete the project within a week, please submit your proposal.