Method for detecting significance of stereo image based on human eye stereo visual characteristics

A technology of stereo vision and stereo images, applied in the field of image processing, can solve the problems of inapplicability to the saliency detection of stereo images, and the distance information of objects is not considered.

Inactive Publication Date: 2017-05-31
HANGZHOU DIANZI UNIV
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Problems solved by technology

[0003] Most of the current saliency calculation models only use spatial two-dimensional information such as image color, brightness, shape, and texture as input, and then perform saliency calculations based on pixel points

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  • Method for detecting significance of stereo image based on human eye stereo visual characteristics
  • Method for detecting significance of stereo image based on human eye stereo visual characteristics
  • Method for detecting significance of stereo image based on human eye stereo visual characteristics

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Embodiment Construction

[0067] The present invention will be further described in detail in conjunction with the following specific embodiments and accompanying drawings.

[0068] The purpose of the present invention is exactly to propose a kind of stereoscopic image saliency detection method based on binocular stereovision, comprises the steps:

[0069] Step 1: Salient feature extraction: perform saliency calculation from the two-dimensional and depth view information of the stereo image, and extract two-dimensional salient regions and depth salient regions respectively;

[0070] The extraction of two-dimensional salient regions specifically includes the following steps:

[0071] First, the SLIC algorithm is used to preprocess the left view of the stereoscopic view, and the superpixel region is obtained through region segmentation and the region similarity is merged. Then, the GBVS model is used for two-dimensional saliency calculation. The specific steps are as follows:

[0072] c) Using the SLIC ...

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Abstract

The invention particularly relates to a method for detecting significance of a stereo image based on human eye stereo visual characteristics. The method comprises the following steps of calculating the significance of view information of two different dimensions (space and depth) of a stereo image; firstly, using an SLIC (simple linear iterative clustering) algorithm to perform ultrapixel segmentation on a single-viewpoint view, and combining similarity of areas; then, using a GBVS (graph-based visual saliency) algorithm to calculate a two-dimensional space significance map; combining the absolute parallax feature, local parallax feature and depth contrast feature in a parallax map to perform depth significant calculation; finally, combining with human eye visual fatigue characteristics to reasonably process the parallax distribution, clustering the significance of the two different dimensions of significance maps by a linear weighting type, and generating a stereo image significance map. The method can be used for effectively detecting the significance area of the stereo image under different scenes, and is suitable for the fields of doubtful object calculation, image searching and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for detecting the saliency of a stereoscopic image based on binocular stereovision of human eyes. Background technique [0002] Saliency detection technology is an important part of stereoscopic video processing technology and is also the basis of many different applications in image processing, especially in important applications such as object detection and recognition, image compression, visual navigation and image quality assessment. For example, it can be obtained by The salient detection technology obtains the visually salient areas of the stereoscopic video, further improves the video image quality of the visually salient areas, and reduces the processing time of the non-salient areas (that is, areas that have less impact on the human visual system). [0003] Most of the current saliency calculation models only use spatial two-dimensional inf...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11
CPCG06T7/0002G06T2207/10012G06T2207/20221
Inventor 刘晓琪周洋何永健
Owner HANGZHOU DIANZI UNIV
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