PERCEPTUAL-BASED HYPERSPECTRAL IMAGE FUSION USING MULTIRESOLUTION ANALYSIS

A perceptual-based multiresolution image fusion technique is demonstra ted using the Airborne Visible and Infrared Imaging Spectrometer (AVIR IS) hyperspectral sensor data. The AVIRIS sensor, which simultaneously collects information in 224 spectral bands that range from 0.4 to 2.5 mu m in approximately IO-nm increments, produces 224 images, each rep resenting a single spectral band. The fusion algorithm consists of thr ee stages. First, a Daubechies orthogonal wavelet basis set is used to perform a multiresolution decomposition of each spectral image. Next, the coefficients from each image are combined using a perceptual-base d weighting. The weighting of each coefficient, from a given spectral band image, is determined by the spatial-frequency response (contrast sensitivity) of the human visual system. The spectral image with the h igher saliency value, where saliency is based on a perceptual energy, will receive the larger weight. Finally, the fused coefficients are us ed for reconstruction to obtain the fused image. The image fusion algo rithm is analyzed using test images with known image characteristics a nd image data from the AVIRIS hyperspectral sensor. By analyzing the s ignal-to-noise ratios and visual aesthetics of the fused images, contr ast-sensitivity-based fusion is shown to provide excellent fusion resu lts and to outperform previous fusion methods.