Method for performing image processing applications using quadratic programming
View Patent ↗A method performs an image processing application by expressing the image processing application as a non-negative quadratic program (NNQP) with a quadratic objective, and nonnegativity constraints. A Karush-Kuhn-Tucker condition of the NNQP is expressed as a fixpoint ratio. Then, the fixpoint ratio is determined iteratively until a solution to the image processing application is reached with a desired precision.
1. A method for performing an image processing application, comprising the steps of:
expressing the image processing application as a non-negative quadratic program (NNQP) with a quadratic objective, and nonnegativity constraints;
expressing a Karush-Kuhn-Tucker condition of the NNQP as a fixpoint ratio; and
determining iteratively the fixpoint ratio until a solution to the image processing application is reached with a desired precision, wherein the solution to the image processing application is an output image produced by the image processing application, and
wherein steps are performed in a processor.
2. The method of claim 1 , wherein the NNQP has linear constraints.
3. The method of claim 1 , wherein an input to the image processing application is a set of low-resolution images, and the fixpoint ratio is a non-negative least squares (NNLS) iterator, and the solution is a high-resolution image.
4. The method of claim 1 , wherein an input to the image processing application is a set of partially labeled images, and the fixpoint ratio is a non-negative least squares (NNLS) iterator, and the solution is a set of completely labeled images.
5. The method of claim 1 , wherein an input to the image processing application is a blurred image, and the fixpoint ratio is a non-negative least squares (NNLS) iterator, and the solution is a deblurred image.