Device and method for estimating if an image is blurred
First Claim
1. A method for estimating if an image is blurred or sharp, the method comprising the steps of:
- determining an image gradient histogram distribution of at least a portion of the image; and
comparing at least a portion of the image gradient histogram distribution to a Gaussian model of at least a portion of the image to estimate if the image is either blurred or sharp.
1 Assignment
0 Petitions
Accused Products
Abstract
A method for estimating if an image (14) is either blurred or sharp includes the steps of (i) determining an image gradient histogram distribution (410) of at least a portion of the image (14), and (ii) comparing at least a portion of the image gradient histogram distribution (410) to a Gaussian model gradient histogram distribution (414) of at least a portion of the image (14) to estimate if the image (14) is either blurred or sharp. In most cases, a sharp image (14) has a relatively large tailed distribution when compared to the Gaussian model, while a blurred image has a relatively small tailed distribution when compared to the Gaussian model.
-
Citations
28 Claims
-
1. A method for estimating if an image is blurred or sharp, the method comprising the steps of:
-
determining an image gradient histogram distribution of at least a portion of the image; and comparing at least a portion of the image gradient histogram distribution to a Gaussian model of at least a portion of the image to estimate if the image is either blurred or sharp. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
-
-
10. A method for estimating if an image is blurred or sharp, the method comprising the steps of:
-
blurring the image to create an artificially blurred image; determining an image gradient histogram distribution for at least a portion of the image; determining an image gradient histogram distribution for at least a portion of the artificially blurred image; and comparing at least a portion of the image gradient histogram distribution of the image to at least a portion of the image gradient histogram distribution for the artificially blurred image to compute a distribution probability difference to estimate if the image is either blurred or sharp.
-
-
11. A device for estimating if an image is either blurred or sharp, the device comprising:
a control system including a processor that (i) determines an image gradient histogram distribution of at least a portion of the image; and
(ii) compares at least a portion of the image gradient histogram distribution to a Gaussian model of at least a portion of the image to estimate if the image is either blurred or sharp.- View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
-
20. A method for estimating a blur degree of an image, the image having a Gaussian model, the method comprising the steps of:
-
determining an image gradient histogram distribution of at least a portion of the image; and comparing at least a portion of the image gradient histogram distribution to at least a portion of the Gaussian model to estimate the blur degree of the image. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28)
-
Specification