In this paper, image fusion algorithm are used to improve the quality of HJ-1 B IRS LST products. The HJ-1 B IRS LST
data with multi temporal are transformed to the similar temporal based on a fusion framework, and the MODIS LST
products are used as reference data. There are two research core: 1) How to simplify the fusion model to obtain more
robustness data production result; 2)How to deal with the cloud and cloud shadow region. A algorithm process for HJ-1
B LST products is proposed, and a specific experiment showed the application prospect of the algorithm process.
The HJ-1 A and HJ-1 B satellites were launched on September 6, 2008 from China. The radiometric normalization of charge coupled device (CCD) images is still challenging work. In this paper, an automatic algorithm for relative radiometric normalization between HJ-1A/B CCD images and Landsat TM is presented. This method directly normalizes the digital numbers (DN) of HJ-1A/B CCD images, band by band, to surface reflectance. A united linear relationship between the DN of the target images and the surface reflectance of the referenced images was derived, and the applicable conditions are described here. The iteratively reweighted modification of the multivariate alteration detection (IR-MAD) transformation was used to automatically select pseudoinvariant features (PIFs). This procedure is simple, fast, and completely automatic. The algorithm was applied to normalize three subregions of different HJ-1A/B CCD images. The results show that the retrieval quality of the surface reflectance does meet the requirements of quantitative remote sensing.