17993357. Restoring Images Using Deconvolution simplified abstract (Samsung Electronics Co., Ltd.)

Restoring Images Using Deconvolution

Organization Name

Samsung Electronics Co., Ltd.

Inventor(s)

Changgeng Liu of San Jose CA (US)

Luxi Zhao of Toronto (CA)

Ziwen Jiang of Sunnyvale CA (US)

Abdelrahman Abdelhamed of Toronto (CA)

Abhijith Punnappurath of North York (CA)

Ye Zhao of Sunnyvale CA (US)

Ernest Rehmatulla Post of San Francisco CA (US)

Michael Brown of Toronto (CA)

Sajid Sadi of San Jose CA (US)

Restoring Images Using Deconvolution - A simplified explanation of the abstract

This abstract first appeared for US patent application 17993357 titled 'Restoring Images Using Deconvolution

Simplified Explanation

The patent application describes a method for image restoration using point-spread functions (PSFs) and deconvolution techniques. Here is a simplified explanation of the abstract:

• Access image patches and corresponding PSFs
• Deconvolve image patches with PSFs
• Determine weights for portions of image patches
• Interpolate deconvolved image patches based on weights to generate a restored image patch

Potential Applications

The technology described in this patent application could be applied in various fields such as medical imaging, satellite imaging, and digital photography for enhancing image quality and clarity.

Problems Solved

This technology addresses the challenge of image degradation caused by factors like blurring or noise, by effectively restoring the original image quality through deconvolution and interpolation techniques.

Benefits

The benefits of this technology include improved image quality, enhanced details, and better visualization of images in various applications.

Potential Commercial Applications

The technology could find commercial applications in industries such as healthcare, surveillance, remote sensing, and photography for developing advanced imaging systems and software solutions.

Possible Prior Art

One possible prior art in this field is the use of deconvolution algorithms in image processing to enhance image quality and remove distortions. Another could be the application of interpolation techniques for image restoration in various domains.

How does this technology compare to existing image restoration methods in terms of computational efficiency and accuracy?

This article does not provide a direct comparison with existing methods in terms of computational efficiency and accuracy. Further research or testing may be needed to evaluate the performance of this technology against other image restoration techniques.

What are the limitations or constraints of this technology in real-world applications?

The article does not discuss the limitations or constraints of this technology in real-world applications. Understanding the potential challenges or restrictions of implementing this method could provide a more comprehensive view of its practicality and effectiveness.

Original Abstract Submitted

In one embodiment, a method includes generating, from an accessed image, one or more image patches, and for each image patch: (1) accessing a set of point-spread functions (PSFs), wherein each PSF in the set of PSFs corresponds to one of a plurality of points in the image patch; (2) generating a set of deconvolved image patches by deconvolving the image patch with each PSF from the set of PSFs for that patch; (3) determining, for each of one or more portions of the image patch, a set of weights, wherein each weight in the set of weights is associated with one of the deconvolved image patches; and (4) generating a restored image patch by interpolating the set of deconvolved image patches based on the set of weights.