Abstract: Systems and methods for real-time image deblur and stabilization can utilize sensor data for estimating motion blur without the high computational cost of image analysis techniques. The estimated motion blur can then be utilized to generate a motion blur kernel for image correction. The systems and methods can further refine the correction by processing the motion blur kernel with a polynomial filter to generate a sharpening kernel. The systems and methods can provide for real-time correction even with minimal to no stabilization masking.

Abstract: Systems, apparatus, and methods are presented for deblurring images. One method includes receiving an image and estimating blur for the image. The method also includes applying a deblurring filter to the image and reducing halo from the image.

Abstract: System and Method for automatically removing blur and noise in a plurality of digital images. The system comprises an electronic processor configured to receive the plurality of digital images, perform motion estimation and motion compensation to align the plurality of digital images, determine an alignment of the plurality of digital images with respect to a reference frame, generate a consistency map based on the alignment of the plurality of digital images with respect to the reference frame, combine the plurality of digital images aligned with respect to the reference frame in the Fourier domain using a quality of alignment information from the consistency map to generate an aggregated frame, and apply a post-processing filter to enhance the quality of the aggregated frame.

Abstract: System and Method for automatically removing blur and noise in a plurality of digital images. The system comprises an electronic processor configured to receive the plurality of digital images, perform motion estimation and motion compensation to align the plurality of digital images, determine an alignment of the plurality of digital images with respect to a reference frame, generate a consistency map based on the alignment of the plurality of digital images with respect to the reference frame, combine the plurality of digital images aligned with respect to the reference frame in the Fourier domain using a quality of alignment information from the consistency map to generate an aggregated frame, and apply a post-processing filter to enhance the quality of the aggregated frame.

Abstract: An image rendering method comprising the steps of: (a) performing a noisy estimation of a given view of a given scene of said image using a Monte-Carlo stochastic renderer, wherein general information of each ray sample, such as color and position in the image plane, is stored, (b) calculating a similarity measure between two sets of samples cast from two pixels of said scene and their neighbors, and (c) generating an output image wherein each pixel color is a weighted combination of the pixel colors generated from (a) with weights based on the similarity measure of (b) between the respective set of samples cast from the pixels and their neighbors.

Abstract: An image rendering method comprising the steps of: (a) performing a noisy estimation of a given view of a given scene of said image using a Monte-Carlo stochastic renderer, wherein general information of each ray sample, such as color and position in the image plane, is stored, (b) calculating a similarity measure between two sets of samples cast from two pixels of said scene and their neighbors, and (c) generating an output image wherein each pixel color is a weighted combination of the pixel colors generated from (a) with weights based on the similarity measure of (b) between the respective set of samples cast from the pixels and their neighbors.