Image nonuniformity correction method based on Laplace operator and deconvolution

A non-uniformity correction and deconvolution technology, which is applied in image enhancement, image data processing, calculation, etc., can solve the problems of low correction accuracy and weak robustness, and achieve simple calculation, strong robustness, and strong The effect of engineering application value

Active Publication Date: 2017-06-23
CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
View PDF5 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems of low correction accuracy and weak robustness in the existing non-uniformity correction methods, the present invention proposes an image non-uniformity correction method based on Laplace operator and deconvolution

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
  • Image nonuniformity correction method based on Laplace operator and deconvolution
  • Image nonuniformity correction method based on Laplace operator and deconvolution
  • Image nonuniformity correction method based on Laplace operator and deconvolution

Examples

Experimental program
Comparison scheme
Effect test

example

[0052] to combine Figure 2 to Figure 4 To illustrate this example, this example applies an image non-uniformity correction method based on Laplace operator and deconvolution of the present invention to the principle prototype. The principle prototype includes an optical lens with a focal length of 38mm and a cooled long-wave infrared detector produced by Sofradir. Among them, the resolution of the detector is 320×256, and the response band is 7.7-11.3 μm.

[0053] First, use the turntable to continuously change the azimuth angle of the prototype, collect and store 1001 frames of original infrared images, one of which is as follows: figure 2 shown.

[0054] Secondly, the above 1001 frames of original images are convolved using the Laplace convolution kernel in formula (3), and the boundary of the image is symmetrically extended.

[0055] Again, for the convolved image, calculate the median of the 1001 values ​​corresponding to each pixel to obtain the median matrix

[0...

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 present invention provides an image nonuniformity correction method based on a Laplace operator and deconvolution. The method comprises the steps of (1) carrying out convolution processing on an F frame image to be corrected by using the Laplace operator, (2) obtaining the median of a same pixel of the F frame image after convolution, and carrying out pixel-by-pixel calculation to obtain a median matrix, and (3) calculating a correction coefficient matrix b by using a deconvolution algorithm based on the mean value matrix, and correcting the image to be corrected by using the correction coefficient matrix b. Based on the assumption that four adjacent pixels have statistical consistency, the convolution and median taking are carried out on the image to finally calculate the correction coefficient matrix to carry out correction. According to the method, a high frequency component and a low frequency component in nonuniformity noise can be corrected, the storage of a correction coefficient based on a calibration method in advance is not needed, and thus a problem of the drift of detector radiation response with time is solved thoroughly.

Description

technical field [0001] The invention belongs to the technical field of infrared focal plane imaging, and in particular relates to an image non-uniformity correction method based on Laplace operator and deconvolution. Background technique [0002] The long-wave infrared detector has the characteristics of simple structure, small size, high sensitivity and passive imaging, and is widely used in the fields of industry, agriculture, medical treatment, forest fire prevention and national defense. Due to the limitations of semiconductor materials and process conditions, the radiation response of each pixel is different, causing the detector to be interfered by serious non-uniform noise, which reduces the spatial resolution of the system and seriously affects the imaging quality of the system. Compared with linear array detectors, infrared focal plane arrays are more susceptible to non-uniform noise; compared with short-wave and mid-wave infrared detectors, long-wave infrared detec...

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 Applications(China)
IPC IPC(8): G06T5/00G06T5/20
CPCG06T5/20G06T2207/10048G06T5/70
Inventor 王德江周达标霍丽君刘让贾平
Owner CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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