Hyperspectral and Panchromatic Image Fusion via Adaptive Tensor and Multi-Scale Retinex Algorithm

Fusion of panchromatic image (PANI) and hyperspectral image (HSI) to obtain an output image with high spatial and spectral resolutions has received increasing interests recently. We propose a new image fusion method for HSI and PANI by combining adaptive tensor with a multi-scale Retinex algorithm in this paper. In the proposed method, an adaptive tensor based method is presented to effectively extract the structure information of HSI, and multi-scale Retinex algorithm is introduced to obtain the spatial and structure details of PANI. To integrate spatial structure information, a gradient-based weighted fusion strategy is proposed to combine spatial details of HSI and PANI. The integrated structure details are injected to generate the fused HSI. Experiments using both simulated and real remote sensing data sets demonstrated that the proposed fusion algorithm performs better than the state-of-the-art algorithms in visual inspection and objective assessment.