How to deal with large multispectral images comparison? PCA score distribution as a tool

Key Points

• Multispectral image comparison provides essential insights for various applications, enhancing data analysis efficiency.
• The PCA score distribution facilitates understanding the dimensionality and variance in large datasets of images.
• Observational analysis focuses on the performance of PCA methods for managing and comparing multispectral images.
• This approach highlights the necessity for advanced techniques in handling large image datasets, as limitations may arise in traditional methods.

Abstract