Image deblurring using a combined differential image
First Claim
1. A method for determining a deblurred image, the method implemented at least in part by a data processing system and comprising:
- a) receiving a blurred image of a scene;
b) receiving a blur kernel;
c) initializing a candidate deblurred image;
d) determining a plurality of differential images representing differences between neighboring pixels in the candidate deblurred image, wherein each pixel of a particular differential image is determined by computing a difference between the corresponding pixel in the candidate deblurred image and a nearby pixel in the candidate deblurred image at a predefined relative position, wherein each differential image is associated with a different predefined relative position;
e) determining a combined differential image by combining the differential images;
f) updating the candidate deblurred image responsive to the blurred image, the blur kernel, the candidate deblurred image and the combined differential image, wherein the candidate deblurred image is updated by using a Bayesian inference method that evaluates candidate deblurred images using an energy function that includes an image differential term which is a function of the combined differential image;
g) repeating steps d)-f) until a convergence criterion is satisfied; and
h) storing the final candidate deblurred image in a processor-accessible memory system.
5 Assignments
0 Petitions
Accused Products
Abstract
A method for determining a deblurred image comprising: receiving a blurred image of a scene; receiving a blur kernel; initializing a candidate deblurred image; determining a plurality of differential images representing differences between neighboring pixels in the candidate deblurred image; determining a combined differential image by combining the differential images; repeatedly updating the candidate deblurred image responsive to the blurred image, the blur kernel, the candidate deblurred image and the combined differential image until a convergence criterion is satisfied; and storing the final candidate deblurred image in a processor-accessible memory system.
21 Citations
18 Claims
-
1. A method for determining a deblurred image, the method implemented at least in part by a data processing system and comprising:
-
a) receiving a blurred image of a scene; b) receiving a blur kernel; c) initializing a candidate deblurred image; d) determining a plurality of differential images representing differences between neighboring pixels in the candidate deblurred image, wherein each pixel of a particular differential image is determined by computing a difference between the corresponding pixel in the candidate deblurred image and a nearby pixel in the candidate deblurred image at a predefined relative position, wherein each differential image is associated with a different predefined relative position; e) determining a combined differential image by combining the differential images; f) updating the candidate deblurred image responsive to the blurred image, the blur kernel, the candidate deblurred image and the combined differential image, wherein the candidate deblurred image is updated by using a Bayesian inference method that evaluates candidate deblurred images using an energy function that includes an image differential term which is a function of the combined differential image; g) repeating steps d)-f) until a convergence criterion is satisfied; and h) storing the final candidate deblurred image in a processor-accessible memory system. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
-
-
17. A digital camera system comprising:
-
an image sensor for capturing an image of a scene; an lens system for imaging the scene onto the image sensor; a processor-accessible memory system; and a data processing system for performing the steps of; a) receiving a blurred image of a scene; b) receiving a blur kernel; c) initializing a candidate deblurred image; d) determining a plurality of differential images representing differences between neighboring pixels in the candidate deblurred image, wherein each pixel of a particular differential image is determined by computing a difference between the corresponding pixel in the candidate deblurred image and a nearby pixel in the candidate deblurred image at a predefined relative position, wherein each differential image is associated with a different predefined relative position; e) determining a combined differential image by combining the differential images; f) updating the candidate deblurred image responsive to the blurred image, the blur kernel, the candidate deblurred image and the combined differential image, wherein the candidate deblurred image is updated by using a Bayesian inference method that evaluates candidate deblurred images using an energy function that includes an image differential term which is a function of the combined differential image; g) repeating steps d)-f) until a convergence criterion is satisfied; and h) storing the final candidate deblurred image in the processor-accessible memory system.
-
-
18. A computer program product for determining a deblurred image comprising an executable software application stored in a non-transitory process readable medium for causing a data processing system to perform the steps of:
-
a) receiving a blurred image of a scene; b) receiving a blur kernel; c) initializing a candidate deblurred image; d) determining a plurality of differential images representing differences between neighboring pixels in the candidate deblurred image, wherein each pixel of a particular differential image is determined by computing a difference between the corresponding pixel in the candidate deblurred image and a nearby pixel in the candidate deblurred image at a predefined relative position, wherein each differential image is associated with a different predefined relative position; e) determining a combined differential image by combining the differential images; f) updating the candidate deblurred image responsive to the blurred image, the blur kernel, the candidate deblurred image and the combined differential image, wherein the candidate deblurred image is updated by using a Bayesian inference method that evaluates candidate deblurred images using an energy function that includes an image differential term which is a function of the combined differential image; g) repeating steps d)-f) until a convergence criterion is satisfied; and h) storing the final candidate deblurred image in a processor-accessible memory system.
-
Specification