In this paper

an automatic and robust image mosaic algorithm is presented. In this algorithm

Harris corner detector is used to extract feature points

which gains sub pixel precision for features extraction. Then

a pseudo matching set is obtained by comparing local neighborhoods of features through intensity cross correlation method and these pseudo matches are divided into inliers and outliers using robust RANSAC algorithm. In the inliers sub set

LM algorithm is used to estimate the point transformation matrix between two images accurately. In the end

the image color of the overlapping band is smoothed with bilinear interpolation technique. The whole algorithm is completed automatically. It filters the noisy or wrong input data iteratively

then estimates the model parameters through pure data

so it has strong error tolerant capacity for the image noise and inaccuracy of feature extraction. When estimating the model parameters

the energy function is constructed based on the position errors of features instead of the features' intensity errors

which conquers the original methods' shortcoming of sensitivity to illuminating conditions and makes this algorithm more practical. Experimental results show the image mosaic effect is wonderful and the algorithm is stable very much. It is high valuable in practice.