Apparatus, system, and method for multi-patch based super-resolution from an image

a multi-patch, image technology, applied in the field of image and video processing, can solve the problems of difficult hardware implementation, noisy images and irregularities along curved edges, and the use of large databases is more time and memory-consuming, so as to achieve comparable hr image quality and reduce computation complexity of methods
US20140093185A1Active Publication Date: 2014-04-03HONG KONG APPLIED SCI & TECH RES INST
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Patent Information

Authority / Receiving Office
US · United States
Patent Type
Applications(United States)
Current Assignee / Owner
HONG KONG APPLIED SCI & TECH RES INST
Publication Date
2014-04-03

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Abstract

Embodiments of the present invention include apparatuses, systems and methods for multi-patch based super-resolution from a single video frame. Such embodiments include a scale-invariant self-similarity (SiSS) based super-resolution method. Instead of searching HR examples in a database or in LR image, the present embodiments may select the patches according to the SiSS characteristics of the patch itself, so that the computational complexity of the method may be reduced because there is not any search involved. To solve the problem of lack of relevant examples in natural images, the present embodiments may employ multi-shaped and multi-sized patches in HR image reconstruction. Additionally, embodiments may include steps for a hybrid weighing method for suppressing artifacts. Advantageously, certain embodiments of the method may be 10˜1,000 times faster than the example based SR approaches using patch searching and can achieve comparable HR image quality.
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Description

TECHNICAL FIELD

[0001] The present invention relates generally to image and video processing and, more particularly, to apparatuses, systems, and methods for super-resolution from an image.BACKGROUND OF THE INVENTION

[0002] Super-resolution (SR) methods aim to recover new high-resolution (HR) information beyond the Nyquist frequency of the low-resolution (LR) image. SR methods are applicable in relation to HDTV, video communication, video surveillance, medical imaging, and other applications. Recently, example-based SR (also commonly referred to as “hallucination”) that reconstructs HR image from one single LR input image has emerged as a promising technology because it can overcome some limitations of the classical multi-image super-resolution methods and can be implemented with lower computation and memory costs.

[0003] Example-based SR methods assume that the missing HR details can be learned and inferred from a representative training set or the LR image itself. For example, an image ...

Claims

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