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

A technology of super-resolution reconstruction and convex set projection, which is applied in image enhancement, image data processing, instruments, etc., and can solve problems such as functioning, loss of detail information, and low-resolution images

Inactive Publication Date: 2011-02-23
上海格州电子股份有限公司
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  • 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

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  • 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

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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. Such as 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. Such as 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 refe...

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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

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Application Information

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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
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