Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

An image saliency detection method using red-black wavelet transform

A red-black wavelet and detection method technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problems of difficulty in obtaining salient region segmentation results and low fineness of saliency maps, and achieve high fineness and improved The effect of accuracy

Inactive Publication Date: 2017-02-15
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] The purpose of the present invention is to solve the problem that the saliency map in the traditional frequency domain analysis method has low fineness and it is difficult to obtain a good saliency region segmentation result, and proposes an image saliency detection method using red-black wavelet transform

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • An image saliency detection method using red-black wavelet transform
  • An image saliency detection method using red-black wavelet transform
  • An image saliency detection method using red-black wavelet transform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0049] Example: Image Saliency Detection. This method is used and tested on the ASD dataset, which contains 1000 pictures, and the corresponding salient region maps manually calibrated.

[0050] Step 1. Read the image I in the data set, determine the number of transformation layers of the red-black wavelet according to the size of the image I, and perform the red-black wavelet transform on the image I to obtain T.

[0051] In order to remove the influence of noise on the detection results, the original image size is reduced to 1 / 4 of the original size, and the number of wavelet transform layers is determined according to the reduced size. For example, a 300×400 image becomes 150×200 after shrinking. According to formula (1), the number of transformation layers can be obtained as L=[log 2 min(150,200)] floor -1=6. According to the number of transformation layers, red-black wavelet transformation is performed on the image. In this embodiment, wavelet transform processing is ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to an image significance detection method utilizing red-black wavelet transform, and belongs to the technical field of image analysis and processing. The method comprises the following steps that according to the size of an image I, the number of decomposition layers of red-black wavelets is determined, and the image I is subjected to red-black wavelet transform to obtain T; the image I is subjected to Gaussian smoothing processing and then red-black wavelet transform to obtain Tsmooth; the difference r between two results of red-black wavelet transform is calculated, r= Tsmooth-T, and r is subjected to red-black wavelet transform to obtain a significance image s; s is subjected to binary segmentation to obtain a significance detection result. Compared with a traditional frequency-domain analysis method, the method effectively improves accuracy of image significance detection.

Description

technical field [0001] The invention relates to an image saliency detection method, in particular to an image saliency detection method using red-black wavelet transform, and belongs to the technical field of image analysis and processing. Background technique [0002] In the field of images, saliency refers to the human beings capture the most interesting regions in the scene through visual perception. Image saliency detection aims to find out the salient area (foreground) in the input image, separate it from the background or mark it. Saliency detection can provide support for other image-related work, such as image segmentation, object recognition, image labeling, image adaptive compression, and so on. [0003] At present, the most widely used technique to solve the image saliency detection problem is to utilize the bottom-up approach, the basic idea of ​​which is to assume that the characteristics of the foreground (such as color, intensity, spatial position, etc.) are ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T5/00
CPCG06T7/0002G06T2207/20064
Inventor 赵三元沈建冰李凤霞王清云
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com