Semi-Blind Deblurring Images Captured With An Electronic Rolling Shutter Mechanism

The electronic rolling shutter mechanism found in many digital cameras may result in spatially-varying blur kernels if camera motion occurs during an imaging exposure. However, existing deblurring algorithms cannot remove the blurs in this case since the blurred image doesn't typically meet the assumptions embedded in these algorithms. This paper attempts to address the problem of modeling and correcting nonuniform image blurs caused by the rolling shutter effect. We introduce a new operator and a mask matrix into the projective motion blur model to describe the blurring process of each row in the image. Based on this modified geometric model, an objective function is formulated and optimized in an alternating scheme. In addition, noisy accelerometer data along x and y directions is incorporated as a regularization term to constrain the solution. The effectiveness of this approach is demonstrated by experimental results on synthetic and real images.