Image fusion algorithm based on adaptive weighted coefficients

Image fusion is a very important step for image mosaic. Fusion algorithms affect the visual effect and quality of the mosaic images directly. This paper presents an adaptive weighted coefficients algorithm for image fusion. The algorithm can adjust weighted coefficients adaptively along with changes of the range and shape of the overlapping regions. First, Harris operator is used to detect feature points. Then, we use normalized cross correlation (NCC) and random sample consensus (RANSAC) algorithm to carry out coarse matching and precise matching respectively, and to obtain the transformation matrix. Finally, the proposed algorithm is used to fuse images. Compared with other fusion algorithms, the experiment results indicate that the proposed fusion algorithm eliminates stitching seams more effectively, and has better fusion effect.