System for Hyperspectral Data Analysis, Visualization and Fresco Deterioration Detection

In this paper we proposed a scalable interactive system for fresco deterioration detection by hyper-spectral image data analysis. The system integrates data mining and visualization algorithm and process the hyper-spectral big data from fresco efficiently and conveniently. Firstly, a Geospatial Data Abstraction Library (GDAL) is adapted which provides data reading, image preview and cropping functions, Secondly, the Principal Components Analysis (PCA) algorithm is employed for dimension reduction and compression, Then, the partial least squares (PLS) algorithm is used for training the fresco deterioration detection model. Finally, the predicted results are visualized by using popular visualization method. Experimental results show that the proposed hyper-spectral data analysis system is effectively and efficiently for fresco deterioration detection.