The performance of images captured by traditional camera for motion deblurring is unstable. To tackle the problem, the principle and coded strategy of coded exposure camera are studied, and a novel point spread function (PSF) estimation and motion deblurring approach based on camera-optimized codes and efficient marginal estimation is proposed. Firstly, the alpha matting deblurring approach for traditional camera is investigated, which is extended to coded exposure camera. Then the coded factors influencing deblurring performance are analyzed to find the optimized code fitting for PSF estimation and invertibility. Finally, a PSF estimation approach based on efficient margin and maximum posteriori is modified, and images motion deblurring is accomplished with spatial prior of efficient marginal gradient in a coarse-to-fine way. Experimental results based on simulated and real images show that the proposed algorithm can effectively estimate PSF, and the performance for motion deblurring is superior to that of other existing approaches.