he goal of this project is to achieve high quality real-time motion deblurring for images captured by cameras mounted on mobile devices. First, we will propose a novel two-camera technique that exploits the trade-off between spatial and temporal resolutions in capturing the photo with the camera movement information to be used in the deblurring process. Second, we will introduce new point-spread function (PSF) estimation algorithms by employing the motion information captured by the two-camera imaging device. Third, we will develop new deconvolution algorithms suitable for mobile devices. Finally, we will propose a formal performance evaluation methodology framework for image deblurring in mobile devices. Our research will exploit the results of Ben Ezra’s approach [13]. The system is made up of two cameras whose focal points are similar. The primary camera is a high-resolution camera that is used to take the picture. The secondary camera is a lower resolution imaging device with a high frame rate. The secondary camera is employed to capture the motion information during the exposure time of the primary camera. The temporal information captured by the secondary camera is used to enhance the picture taken by the primary camera by removing motion blur caused by device movement.