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Self-adaption light compensation video image splicing method

A technology of video image and light compensation, which is applied to the details of image stitching, image data processing, graphics and image conversion, etc., and can solve problems such as stitching errors, low resolution, and uneven light

Inactive Publication Date: 2016-07-27
CHANGCHUN UNIV OF SCI & TECH
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a video image splicing method for adaptive light compensation, which uses a scale-invariant feature transformation algorithm, a random sampling consensus algorithm, an adaptive light compensation algorithm, and a fast calculation method for a transfer matrix to perform high-precision matching on video images to be spliced. Real-time splicing of video images with a resolution greater than 640*480 to solve problems such as time-consuming splicing, low resolution, uneven light, and splicing errors caused by camera movement or rotation, achieving the effect of uniform brightness, high resolution, and real-time display

Method used

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  • Self-adaption light compensation video image splicing method
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  • Self-adaption light compensation video image splicing method

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Embodiment Construction

[0087] Include the following steps:

[0088] 1. Collect the video shot by the camera, and extract the first frame image pair of the video;

[0089] 2. Extract the feature points of the video image;

[0090] (1) Generation of scale space

[0091] Scale space is the spatial transformation preprocessing of the image, which is convenient for better calculation and processing. The scale space is calculated by convolution of the Gaussian function with varying scales and the original image;

[0092]

[0093]

[0094] Among them, L(x,y,σ) represents the scale space, I(x,y) represents the gray value of the image, and G(x,y,σ) represents the Gaussian function. (x, y) represents the spatial coordinates; σ is the scale coordinate, which determines the image clarity of the image, the smaller the σ, the blurrier the image as a whole, and the clearer the details, the better the definition; otherwise, the worse the smoothing effect of the image;

[0095] The Gaussian difference DOG p...

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Abstract

The invention relates to a video image mosaic method for adaptive light compensation, belonging to the field of video image processing. Including collecting the video shot by the camera, extracting the image pair of the first frame of the video, extracting the feature points of the video image, finding the matching feature vector pair, eliminating the mismatching feature point pair, calculating the transfer matrix, adaptive light compensation, and video stitching . The advantage is that it can realize seamless, large viewing angle, and real-time video stitching, and can be widely used in fields such as video conferencing, video surveillance, and robot vision.

Description

technical field [0001] The invention belongs to the field of video image processing. Background technique [0002] In the field of video surveillance, due to the limited field of view of a single image acquisition device, the amount of information obtained is limited, and it is gradually difficult to meet people's daily needs. Video splicing technology can splice video images obtained by multiple surveillance cameras to obtain wide-angle, high-definition images. Therefore, video stitching technology will be gradually applied to military remote sensing, aerial video images, aerospace, traffic safety, medical microscopic video images, industrial development, video and teleconferencing and other fields, and has a wide range of application values. The real-time problem is the difficulty of video stitching technology. [0003] Video stitching methods can be divided into two categories: hardware implementation methods and software algorithm implementation methods. The hardware-...

Claims

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Application Information

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IPC IPC(8): G06T3/40
CPCG06T3/4038G06T2200/32
Inventor 朴燕刘硕周英敏
Owner CHANGCHUN UNIV OF SCI & TECH
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