Low-light-level image target detection method based on texture significance

A low-light image and target detection technology, applied in the field of image processing, can solve problems such as low contrast, poor target outline, and high false alarm rate

Active Publication Date: 2015-02-11
NANJING UNIV OF SCI & TECH
View PDF4 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since low-light images have no color information and low contrast, these methods are often applied to low-light image target detection, with low hit rate, high false alarm rate, and poor target contour

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
  • Low-light-level image target detection method based on texture significance
  • Low-light-level image target detection method based on texture significance
  • Low-light-level image target detection method based on texture significance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0054] Such as figure 1 As shown, the present invention is a low-light image target detection method based on texture saliency, comprising the following steps:

[0055] Step 1: Extract the image roughness feature map as follows:

[0056] 1.1 Calculate the average gray value of the pixels in the active window whose size is 4k×4k in the image,

[0057] A k ( x , y ) = Σ i = x - 2 k x + 2 k - 1 Σ j = y - 2 k y + 2 k - ...

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 a low-light-level image target detection method based on texture significance. The method comprises the steps of: firstly, extracting an image roughness characteristic figure, performing binaryzation characteristic treatment, merging regions belonging to the same target, respectively calculating global significance, local significance and position significance, so as to calculate the texture significance and obtain a texture significant figure, and finally, performing image target detection by utilizing the texture significant figure. The method is characterized in that the target detection is performed through the texture significance by utilizing the characteristic of larger difference between low-light-level image target texture and the background. When the method is used for detecting a low-light-level image target, the target contour is good, and the hit rate is high.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a low-light image target detection method based on texture saliency. Background technique [0002] Low-light technology is an important part of night vision technology. The low-light imaging system uses the natural radiation of night sky light and the reflection of objects to obtain images under the action of an image intensifier, which improves the observation ability of the human eye under weak light conditions. However, unlike ordinary visible light images, it is formed after multiple photoelectric conversions and electron multiplications, and has the characteristics of low contrast, low signal-to-noise ratio, and limited gray scale. These characteristics make the low-light image target suffer from noise interference, the contrast with the surrounding environment is low, the target is not obvious, and the automatic detection of the target is difficult. With the continu...

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
IPC IPC(8): G06T7/00G06K9/46
CPCG06T7/13G06V10/60
Inventor 柏连发张毅金左轮韩静岳江陈钱顾国华
Owner NANJING UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap