Abstract: A flicker detecting method for an image capturing device includes acquiring a first image, wherein pixel values of each row in the first image are acquired during a first period; acquiring a second image, wherein pixel values of each row in the second image are acquired during a second period; generating a third image according to the first image and the second image; and detecting flickers according to the third image; wherein the first period is different from the second period.

Abstract: A flicker detecting method for an image capturing device includes acquiring a first image, wherein pixel values of each row in the first image are acquired during a first period; acquiring a second image, wherein pixel values of each row in the second image are acquired during a second period; generating a third image according to the first image and the second image; and detecting flickers according to the third image; wherein the first period is different from the second period.

Abstract: An image blurring avoiding method for a camera includes obtaining a motion data of the camera; and capturing a picture only when the camera is substantially motionless according to the motion data.

Abstract: A hierarchical motion deblurring method for a single image is provided. In the method, a blur kernel of a target image is calculated and a multi-scale representation for representing the target image and the blur kernel is constructed. Then, a gradient attenuation function and a strong edge suppression function are applied to a residual Richardson-Lucy algorithm, so as to iteratively calculate a residual image between the blur kernel and the target image represented by the representation in each scale and restore the residual image to obtain a first restored image and a second restored image. Finally, the two restored images are compared so as to obtain a motion deblurring image.

Abstract: A hierarchical motion deblurring method for a single image is provided. In the method, a blur kernel of a target image is calculated and a multi-scale representation for representing the target image and the blur kernel is constructed. Then, a gradient attenuation function and a strong edge suppression function are applied to a residual Richardson-Lucy algorithm, so as to iteratively calculate a residual image between the blur kernel and the target image represented by the representation in each scale and restore the residual image to obtain a first restored image and a second restored image. Finally, the two restored images are compared so as to obtain a motion deblurring image.

Abstract: A blind image restoration method restores a motion blurred image and a blur kernel is estimated based on an intrinsic bi-level image region of the motion blurred image. In addition, the blur kernel is iteratively estimated. When the blur kernel is iteratively estimated, bi-level image priors are introduced to achieve better image restoration.