In order to improve the quality of images captured by spaceborne optical remote sensors, a deblurring method based on constrained total-variation regularization is proposed. First of all, the deblurring problem is transformed into a non-blind one via estimation of the point spread function (PSF) using multichannel blind deconvolution. The deblurred image is obtained by applying fast gradient projection algorithm to this non-smooth optimization problem. On the inevitable existence of PSF estimation error and noise, the proposed method does not introduce significant ringing and noise amplification. Experimental results based on panchromatic remote sensing images show that it can preserve mean value and meantime increase the energy of Laplacian from 11.1455 to 57.5541. The structural similarity index between original and deblurred images is up to 0.9824. Both visual effect and evaluation indicators demonstrate that the proposed method can effectively improve the quality of remote sensing images.