Improving remote sensing image fusion based on regularization in wavelet domain

Aim. Ref.4, authored by M. Choi, should and can, in our opinion, be further improved. In the full paper, we explain our improvements in some detail; in this abstract, we just add some pertinent remarks to naming the first two sections. Section 1 is: image fusion based on regularization in wavelet domain. In section 1, we present the regularization conditions as shown in eq. (11) deduced by us. Section 2 is: the fusion algorithm and its implementation. Its three subsections are: the algorithm (subsection 2.1), the rules for fusing wavelet coefficients (subsection 2.2) and the seven-step procedure of our new algorithm. In subsection 2.1, we use the gradient descent technique to iterate the wavelet domain, thus accomplishing the image fusion with the least loss of spectral information and spatial characteristics. In subsection 2.2, we use eq. (16) to compute the fusion coefficients of multi-spectral and panchromatic images. The analysis and comparison of experimental results and statistical results, shown in Fig. 1 and Table 1 respectively and obtained by utilizing the U.S. Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data, point out preliminarily that our algorithm can effectively enhance the spatial characteristics of images and preserve their spectral information.