When remote sensing satellites capture images during movement, the high-speed motion of the satellite camera causes motion blur in the remote sensing images. To solve this problem, this paper proposes a new deblurring algorithm based on the remote sensing image sequence with different integration time obtained in one shooting process. This algorithm used contour edge information extracted from short integration time images to guide the estimation of the blurred kernel of the adjacent long integration time images. Furthermore, the algorithm simplified the complexity of the single blurred kernel estimation through the idea of segmented solution. Additionally, the algorithm used the convolution operation to reconstruct the segmented blurred kernel, which greatly improved the accuracy of the blurred kernel estimation. Experimental results show that the proposed algorithm effectively improves the accuracy of blurred kernel estimation and significantly improves the clarity of blurred remote sensing images after deblurring.