Abstract: A method of detecting faces in a digital image comprises selecting a sub-window of the digital image. Sample regions of the sub-window are then selected. The sample regions are analyzed to determine if the sub-window likely represents a face.

Abstract: Methods for estimating a point spread function of a blurred digital image. One example method includes capturing gyro data during an image exposure time, deriving gyro samples from the gyro data at predetermined gyro sampling times, calculating a motion vector field of the image at each gyro sampling time, approximating an overall image scene motion path by averaging motion paths of selected pixels in the image, and estimating the point spread function from the approximated overall image scene motion path.

Abstract: A method of reducing motion blur in a motion blurred image comprises blurring a guess image based on the motion blurred image as a function of blur parameters of the motion blurred image. The blurred guess image is compared with the motion blurred image and an error image is generated. The error image is blurred and a regularization image is formed based on edges in the guess image. The error image, the regularization image and the guess image are combined thereby to update the guess image and correct for motion blur. A method of generating a motion blur corrected image using multiple motion blurred images, each having respective blur parameters is also provided.