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Parallel analysis method based on fluid motion vector field

A motion vector field and fluid motion technology, applied in image analysis, image enhancement, processor architecture/configuration, etc., can solve the problems of low accuracy, low processing efficiency, and reduce the system processing time of image sequence, to improve performance and performance. Efficiency, the effect of improving accuracy

Inactive Publication Date: 2016-11-09
EAST CHINA NORMAL UNIVERSITY
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Problems solved by technology

[0006] In order to overcome the problems of low processing efficiency and low precision in the process of processing fluid motion image sequences in the existing image sequence processing methods, the present invention proposes a parallel analysis method based on the fluid motion vector field, using the existing morphology Matrix and image sequence gray values ​​construct a gray distribution matrix (Gray Distribution Matrix, referred to as GDM), improve the accuracy of the basic information of the image; improve the denoising algorithm, optimize the gray distribution matrix; improve the energy constraint function, realize New energy-constrained optimization; utilizes the Single Instruction Multiple Threads (SIMT) feature of the Graphic Processing Unit (GPU) to convert the analysis of images containing fluid motion from serial processing to parallel processing processing, which improves the performance, efficiency and accuracy of image processing, and also reduces the time for the system to process image sequences

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  • Parallel analysis method based on fluid motion vector field
  • Parallel analysis method based on fluid motion vector field
  • Parallel analysis method based on fluid motion vector field

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Embodiment

[0045] Such as figure 1 Shown is a schematic flow chart of the analysis process of this embodiment.

[0046] Such as figure 2 Shown is the image sequence including fluid motion to be analyzed in this embodiment, and each image in the image sequence is decomposed into 4×4 small areas of the same size.

[0047] According to the decomposed 4×4 small areas of the same size, construct a corresponding 4×4 gray distribution matrix, let L=25, that is, it contains 26 gray levels, and each gray level represents the gray of a certain interval degree value. Use the corresponding function in the opencv library to obtain the gray value of the image. According to the RGB value of each pixel in the image, the gray value of the image can be obtained, and the range of the gray value is 0-255. In this embodiment, the interval segments of 26 gray levels and their corresponding gray values ​​are shown in the following table:

[0048]

[0049]

[0050] The gray distribution matrix is ​​...

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Abstract

The invention provides a parallel analysis method based on a fluid motion vector field. The method comprises the following steps of decomposing each image of an image sequence into several small areas with a same size; constructing a gray scale distribution matrix; acquiring an initial motion vector field of the image sequence in a parallelization mode; through a new smoothness constraint term, carrying out parallelization processing denoising on the initial motion vector field; through a new energy constraint function, carrying out parallelization processing optimization on the denoised motion vector field; and acquiring a main direction motion vector containing a fluid motion image sequence. By using the fluid motion vector analysis method, an energy optimization technology is combined and a single-instruction multi-thread SIMT characteristic of a graphic processor GPU is used so that a fluid analysis is converted into a parallel state from a serial state; parallelization processing to the image is realized; performance and efficiency of image processing are increased; image processing precision is greatly increased and time for a system to process the image sequence is reduced.

Description

technical field [0001] The invention relates to the field of computer graphics, in particular to a parallel analysis method based on fluid motion vector field. Background technique [0002] In the process of image motion analysis, there are generally two analysis methods: optical flow analysis method and motion vector analysis method. The optical flow analysis method mainly represents the geometric change, and uses the motion change of the pixel intensity value between image sequences to determine the motion change of each pixel in the image, and constructs the motion vector of each pixel in the image; motion vector analysis The method mainly aims at the transformation of the uniform corresponding points between two adjacent frames of images to obtain the motion vector of each pixel, so as to construct a running vector field. [0003] Traditional image sequence processing uses the motion vector analysis method or optical flow analysis method to initialize the representation...

Claims

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Application Information

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IPC IPC(8): G06T7/20G06T5/00G06T1/20
CPCG06T1/20G06T7/20G06T5/70
Inventor 陈铭松王红祥庄涵徐思远宋进忠
Owner EAST CHINA NORMAL UNIVERSITY
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