How would you read hyperspectral images with .hsz format in Matlab?
One of the ways is to use the Hyperspectral Image Analysis Toolbox (HIAT).
The tool is intended for the analysis of hyperspectral and multispectral data. HIAT is a collection of functions that extend the capabilities of the MATLAB numerical computing environment. It has been implemented for the MacIntosh and PC-Windows systems using MATLAB. The purpose of this toolbox is to provide the user with an environment where can utilize different image processing methods for hyperspectral and multispectral data. HIAT provides standard image processing methods such as discriminant analysis, principal component, euclidean distance, and maximum likelyhood.
Toolbox Features
– Image formats for loading and saving: .mat, .bsq, .bil, .bip, .jpg, with ENVI header info and .tiff.
– Pre-Processing algorithms: Resolution Enhancements and Principal Component Analysis Filter.
– Feature Extraction/Selection Algorithms: Principal Components Analysis, Discriminant Analysis, Singular Value Decomposition Band Subset Selection, Information Divergence Band. Subset Selection, Information Divergence Projection Pursuit, Optimized Information Divergence Projection Pursuit.
– Classifiers: Euclidean Distance, Fisher’s Linear Discriminant, Mahalanobis Distance, Maximum Likelihood, Angle Detection.
– Post-Processing Algorithms: supervised and unsupervised ECHO classifier. ECHO (2×2, 3×3, 4×4).
– Supported Platforms: UNIX/Linux, MS-Windows 2000 and XP, Macintosh (OS X 10.1.4 and higher).
– Online help documentation and a hyperspectral data set.
Download the free software for the MATLAB version here.