Pansharpening Based on Total Least Squares Regression and Ratio Enhancement

The key of ratio enhancement (RE) is to synthesize a low-resolution panchromatic image. The grey-level distortion of the synthesized low-resolution image can distort a fused image. To tackle this problem, we propose a pansharpening method based on total least-squares regression and ratio enhancement (TLSR-RE). This method can correct the grey-level distortion in the low-resolution panchromatic synthetic image for different ground objects. The normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) are adopted to classify the pixels into different classes. Then, we employe total least squares (TLS) regression to obtain the error-free panchromatic and multispectral image of each class. The low-resolution panchromatic image is synthesized by weighted summation of the error-free multispectral image. In addition, the grey-level distorted pixels are extracted for further correction. Finally, the multispectral image is sharpened by the ratio enhancement method. The experimental results reveal that the proposed algorithm achieves high-fidelity in spatial details and spectrum.