IP Library Granted Patent US 8,983,183
Granted Patent B2
US 8,983,183 · App. 14/302,747 · Granted Mar 17, 2015

Spatially varying log-chromaticity normals for use in an image process

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Quick Facts
Patent No.
US 8,983,183
App. No.
14/302,747
Granted
Mar 17, 2015
Kind
B2
Abstract

In a first exemplary embodiment, an automated, computerized method is provided for processing an image. The method includes the steps of providing an image file depicting an image defined by image locations, in a computer memory, generating a bi-illuminant chromaticity plane in a log color space for representing the image locations of the image in a log-chromaticity representation for the image, providing a set of estimates for an orientation of the bi-illuminant chromaticity plane and calculating a single orientation for each one of the image locations as a function of the set of estimates for an orientation.

Claims (17)

1. An automated, computerized method for processing an image, comprising the steps of:

providing an image file depicting an image defined by image locations, in a computer memory;

providing a set of estimates for an orientation determined as a function of a bi-illuminant dichromatic reflection model; and

calculating a single orientation for each one of the image locations as a function of the set of estimates for the orientation.

2. The method of claim 1 wherein the step of calculating a single orientation for each one of the image locations as a function of the set of estimates for the orientation is carried out by executing a k-NN algorithm.

3. The method of claim 2 wherein the k-NN algorithm is based upon a weighted function of spatial and spectral distances between the image locations and the set of estimates for an orientation determined as a function of a bi-illuminant dichromatic reflection model.

4. The method of claim 1 wherein the step of calculating a single orientation for each one of the image locations as a function of the set of estimates for an orientation is carried out by solving a system of linear equations representing constraints between values based upon selected ones of the set of estimates for an orientation determined as a function of a bi-illuminant dichromatic reflection model.

5. The method of claim 4 wherein the constraints include constraints selected from the group including a smoothness constraint, a data constraint, an anchor constraint, and combinations thereof.

6. The method of claim 1 wherein the image locations comprise pixels.

7. The method of claim 1 wherein the image locations comprise tokens.

8. A computer program product, disposed on a non-transitory computer readable media, the product including computer executable process steps operable to control a computer to: provide an image file depicting an image defined by image locations, in a computer memory, provide a set of estimates for an orientation determined as a function of a bi-illuminant dichromatic reflection model and calculate a single orientation for each one of the image locations as a function of the set of estimates for the orientation.

9. The computer program product of claim 8 wherein the process step to calculate a single orientation for each one of the image locations as a function of the set of estimates for an orientation is carried out by a process step to execute a k-NN algorithm.

10. The computer program product of claim 9 wherein the k-NN algorithm is based upon a weighted function of spatial and spectral distances between the image locations and the set of estimates for an orientation determined as a function of a bi-illuminant dichromatic reflection model.

11. The computer program product of claim 8 wherein the process step to calculate a single orientation for each one of the image locations as a function of the set of estimates for an orientation is carried out by a process step to solve a system of linear equations representing constraints between values based upon selected ones of the set of estimates determined as a function of a bi-illuminant dichromatic reflection model.

12. The computer program product of claim 11 wherein the constraints include constraints selected from the group including a smoothness constraint, a data constraint, an anchor constraint, and combinations thereof.

13. The computer program product of claim 8 wherein the image locations comprise pixels.

14. The computer program product of claim 8 wherein the image locations comprise tokens.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 7, 2022
From: TANDENT COMPUTER VISION LLC
To: INNOVATION ASSET COLLECTIVE
Reel/Frame 061387/0149 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 3, 2019
From: TANDENT VISION SCIENCE, INC.
To: TANDENT COMPUTER VISION LLC
Reel/Frame 049080/0636 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 11, 2014
From: LALONDE, JEAN-FRANCOIS
To: TANDENT VISION SCIENCE, INC.
Reel/Frame 034145/0713 →