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

Frequency domain registration and convex set projection-based multi-frame image super-resolution reconstruction method

A technology for super-resolution reconstruction and multi-frame images, which is applied in image enhancement, image data processing, instruments, etc. It can solve the problems of low-resolution images, functioning, extracting and analyzing single-frame images, etc.

Inactive Publication Date: 2012-06-27
上海格州电子股份有限公司
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Due to the limitations of the above-mentioned conditions, in each frame of surveillance video data, the target area that people pay attention to has lost most of the detailed information and has become a low-resolution image. Therefore, extracting and analyzing a single frame of image from video data is often Difficult to function in event analysis

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
  • Frequency domain registration and convex set projection-based multi-frame image super-resolution reconstruction method
  • Frequency domain registration and convex set projection-based multi-frame image super-resolution reconstruction method
  • Frequency domain registration and convex set projection-based multi-frame image super-resolution reconstruction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0061] Example: see figure 1 , figure 2 . This multi-frame image super-resolution reconstruction method based on frequency domain registration and convex set projection is characterized in that its specific implementation steps are:

[0062] A. Read in multiple frames of images and select one as a reference frame for registration

[0063] B. Image registration: convert the image to the frequency domain, and in the case of a small offset, only estimate the horizontal and vertical displacement components, ignoring the rotation angle;

[0064] C. Image reconstruction: according to the requested displacement parameters, register the low-resolution image to the high-resolution grid, and perform super-resolution reconstruction using the convex set projection algorithm;

[0065] D. Output image

Embodiment 2

[0067] This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0068] This embodiment first extracts 10 consecutive frames of a video sequence, respectively f 1 (x), f 2 (x)... f 10 (x), the size is 90×90. like Figure 5 Shown is one of ten images selected from the video sequence.

[0069] (1) Image Registration

[0070] (1) For the input image f 1 (x), f 2 (x)... f 9 (x) perform Fourier transform, and select f 1 (x) is used as a reference image, and the others are images for which considerable displacements are to be estimated. The Fourier transform result is F 1 (u)F 2 (u)...F 10 (u).

[0071] (2) According to εU max s -U max Select the spectral range of the image, which is usually in the center third of the image. like Figure 5 shown in blue.

[0072] (3) Calculate the relative displacement between images according to formula 4, using the least squares method.

[0073] The translation parameters of the reference ...

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 discloses a frequency domain registration and convex set projection-based super-resolution reconstruction method. The method comprises the following steps of: reading a multi-frame image, selecting a reference frame serving as registration, and registering the image to obtain relative displacement of each frame of image, wherein a frequency domain-based rapid registration algorithm is used as the registration algorithm; performing super-resolution reconstruction on the multi-frame image by using a convex set projection method according to the relative displacement of each frame;and finally outputting the image, wherein a video sequence sampling speed is high and the displacement of neighboring frames is small, so that by the method, the registration process is simplified, and the translational motion is estimated by using intermediate frequency domain information of the image and the rotation angle is not estimated to greatly reduce the amount of operation of the registration algorithm. Meanwhile, by the method, the convex set projection reconstruction method is simplified, the entire amount of operation of the super-resolution algorithm is greatly reduced by only using high-brightness amplitude constraint of the image and apriori constraint of a Gaussian point spread function, and the reconstruction quality can be guaranteed.

Description

technical field [0001] The invention relates to a multi-frame image super-resolution reconstruction method based on frequency-domain registration and convex set projection. This method mainly uses multi-frame low-resolution images to reconstruct high-resolution images, aiming at improving the resolution of the image , enhance the visual effect of the image, and require less computation, and can be applied to fast image processing equipment. The method can be applied to fields such as medical image processing, remote sensing image reconstruction, and conversion from SDTV to HDTV. Background technique [0002] Super-resolution, in short, is to increase the resolution of images or videos to provide viewers with better visual effects. Super-resolution restoration technology is to estimate a (or a series of) higher-resolution images from a series of low-resolution images, while eliminating additive noise and blurring caused by limited detector size and optical components. It is...

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): G06T5/50
Inventor 万发平刘志丁保焱张兆杨
Owner 上海格州电子股份有限公司
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