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Edge-aware bilateral image processing

An image and reference image technology, applied in image data processing, image enhancement, image analysis, etc.

Active Publication Date: 2018-06-08
GOOGLE LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Such image processing tasks may be computationally intensive (e.g., require significant amounts of time, memory, or other computational resources)

Method used

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Examples

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Embodiment Construction

[0020] Examples of methods and systems are described herein. It should be understood that the words "exemplary," "example," and "illustrative" are used herein to mean "serving as an example, instance, or illustration." Any embodiment or feature described herein as "exemplary," "example," or "illustrative" is not necessarily to be construed as preferred or advantageous over other embodiments or features. Furthermore, the exemplary embodiments described herein are not meant to be limiting. It will be readily appreciated that certain aspects of the disclosed systems and methods can be arranged and combined in a wide variety of different configurations.

[0021] I. Overview

[0022] Example embodiments may facilitate more efficient filtering, upsampling, shading, semantic segmentation, or performing other image processing tasks in an edge-preserving manner. Specifically, color, content, depth, disparity, and / or other image information can be determined based on an input data se...

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Abstract

Example embodiments may allow for the efficient, edge-preserving filtering, upsampling, or other processing of image data with respect to a reference image. A cost- minimization problem to generate anoutput image from the input array is mapped onto regularly- spaced vertices in a multidimensional vertex space. This mapping is based on an association between pixels of the reference image and the vertices, and between elements of the input array and the pixels of the reference image. The problem is them solved to determine vertex disparity values for each of the vertices. Pixels of the output image can be determined based on determined vertex disparity values for respective one or more vertices associated with each of the pixels. This fast, efficient image processing method can be used to enable edge-preserving image upsampling, image colorization, semantic segmentation of image contents, image filtering or de-noising, or other applications.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to and incorporates the contents of US Provisional Patent Application No. 62 / 251,608, filed November 5, 2015. Background technique [0003] When performing image processing on images of natural scenes, it may be beneficial to consider the locations and boundaries of discrete people, animals, plants, objects, buildings, or other content of such images. Such image processing tasks may include filtering of image data (e.g., to remove noise or artifacts), colorization of images, determining information about the content of an image (e.g., the depth of each pixel in an image, the pixel semantic class labels) or some other image processing task. For example, when colorizing an image, it may be beneficial to apply a small number of manually specified color values ​​to the rest of the object to produce a shaded version of the image. In another example, it may be beneficial to filter and / or upsa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06T5/00G06K9/62G06V10/426G06V10/56
CPCG06T2207/10024G06T2207/20028G06V10/426G06V10/56G06V10/761G06F18/22G06T5/73G06T3/4076G06T5/20G06T5/50G06V10/32
Inventor J.T.巴伦B.普尔
Owner GOOGLE LLC
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