Video image super-resolution reconstruction method

A technology of super-resolution reconstruction and video image, which is applied in the field of video image super-resolution reconstruction based on sub-pixel sample sequence and block target motion estimation, which can solve limited problems, and achieve the goal of expanding application fields, improving resolution, improving Effects at cognitive and managerial levels

Inactive Publication Date: 2014-01-01
BAINIAN JINHAI SCI & TECH
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AI Technical Summary

Problems solved by technology

How to extract useful information from these massive data, such as video retrieval, abnormal behavior analysis, etc., the current work is still very limited

Method used

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  • Video image super-resolution reconstruction method

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Experimental program
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Embodiment 1

[0038] see Figure 1 to Figure 5 , the method for super-resolution reconstruction of video images of the present invention, the steps for realizing super-resolution reconstruction of low-resolution video images are as follows:

[0039] 1) For multiple low-resolution images that can be obtained through the same scene, first select the continuous sequence frames of the required video according to the requirements, convert them into static JPG or BMP files, and combine scene parameters, such as CCD pixel resolution, motion displacement and time, select a sub-pixel image of multiple consecutive frames within a pixel;

[0040] 2) According to the image sequence frames of multi-frame sub-pixel images, select the target interest point, and perform the motion estimation of the block target, the steps are as follows:

[0041] (1) Divide the video coding frame into non-overlapping fixed-size motion block targets (Motion Block Target, referred to as MBT), the size is generally 16×16 pix...

Embodiment 2

[0046] see figure 1 - Fig. 6, the video image super-resolution reconstruction method of this embodiment is different from Embodiment 1 in that in step 1), the following steps are used to extract sub-pixel image samples:

[0047] (1) According to the irradiation distance of the on-site video surveillance camera, the focal length of the lens, and the geometric relationship of optical imaging, the running track of the characteristic target is measured and replaced by displacement, and the running speed of the target is calculated according to the time of video monitoring;

[0048] (2) According to the running speed of the target, combined with the pixel resolution of the video surveillance CCD camera, three to five frames of moving images within one pixel are selected as reconstruction frames, and multiple image samples are found in consecutive video frames. The reconstruction frame can select 3 to 11 frames of moving images in one pixel, without affecting the processing result, ...

Embodiment 3

[0052] The video image super-resolution reconstruction method of this embodiment is different from Embodiment 1 or Embodiment 2 in that in step 3), the following interpolation method is used to reconstruct a high-resolution image:

[0053] (1) First estimate the relative motion information between the images of each frame, and obtain the pixel values ​​of the super-resolution image at non-uniformly spaced sampling points,

[0054] (2) Then obtain the pixel values ​​on the super-resolution image grid by non-uniform interpolation, adopt the operation mode of dividing into blocks, divide the image into image blocks of a certain size and quantity, and process each image block separately;

[0055] (3) Then stitch the processed image blocks together to reconstruct a high-resolution image.

[0056] In the video image super-resolution reconstruction method of the present invention, in step 2), the matching criterion for searching for the image block that best matches each moving block...

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Abstract

The invention relates to a video image super-resolution reconstruction method. The method comprises the steps that 1), for a plurality of low-resolution images capable of being obtained through the same scene, continuous sequence frames of needed videos are selected and converted to static JPG or BMP files, and continuous multi-frame sub pixel images in a pixel are selected with the combination of scene parameters; 2) according to the image sequence frames of the multi-frame sub pixel images, a target interest point is selected, and motion estimation of a block-shaped target is conducted; 3) according to a motion estimation result, a non-uniform interpolation reconstruction algorithm is adopted, and a high-resolution image is reconstructed. According to the video image super-resolution reconstruction method, the resolution, on details, of a video image can be improved on the premise that the image quality of an existing imaging device is not improved, the defects in methods for traditional image restoration, enhancement and the like are overcome, and the video image super-resolution reconstruction method has the advantages of being easy and convenient to operate, and high in efficiency. The video image super-resolution reconstruction method can supply optimized image data foundations to the application in the image data field, and therefore the city video information application field can be enlarged.

Description

technical field [0001] The invention relates to a video image processing method, in particular to a video image super-resolution reconstruction method based on sub-pixel sample sequence and block target motion estimation. Background technique [0002] With the development of my country's safe city construction and the start of smart city construction, various video information captured by cameras all over the city has undoubtedly played an important role in ensuring urban safety and improving urban management efficiency. Although the installation of high-definition cameras has greatly improved the quality of still images, the video images obtained in some special scenarios, such as rainy days, foggy days, and large-scale detailed observations of distant scenes, still cannot achieve satisfactory results, especially It is used in some applications that require high on-site information restoration, such as criminal case detection, traffic accident and escape, etc., to obtain in...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50G06T7/20
Inventor 陈长宝杨博雄卢志渊杜红民
Owner BAINIAN JINHAI SCI & TECH
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