Spectral Fidelity Analysis of Compressed Sensing Reconstruction Hyperspectral Remote Sensing Image Based on Wavelet Transformation

Abstract

For hyperspectral image research, spectral characteristic retainment is more important than the spatial details retainment, so it is necessary to evaluate the spectral influence of hyperspectral image compressed sensing. In this paper, the researchers select a hyperspectral remote sensing image PROBE CHRIS with abundant coastal wetland ground objects to analyze spectral fidelity of wavelet transform compressed sensing algorithm on the basis of three indicators between reconstruction and original image pixel spectra: correlation coefficient, error and relative error. Meanwhile, eight typical ground objects are chosen to analyze their respective spectral deviation. The results indicate: (1) Image reconstruction algorithm based on wavelet transform compressed sensing functions well. Between the pixels of reconstruction image and original one, their average spectral correlation coefficient is 0.9428, error is 6.4096, and relative error is 13.81%; (2) Spectrum fidelity indicator values vary with wavebands. Reconstruction algorithm is selective about objects.