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DVS visualization video denoising method based on shared k-svd dictionary

A dictionary and video technology, applied in the field of image processing, can solve problems such as fast denoising, time-consuming dictionary iterative update, etc., and achieve the effect of clear object outline, fast speed and fast denoising speed

Active Publication Date: 2020-10-09
XIDIAN UNIV +1
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Problems solved by technology

Although this method does not require a large number of training samples and can better preserve the object features in the original image, it is difficult to meet the requirements of fast denoising due to the time-consuming iterative update process of the dictionary.

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  • DVS visualization video denoising method based on shared k-svd dictionary
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  • DVS visualization video denoising method based on shared k-svd dictionary

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Embodiment Construction

[0030] The present invention will be described in detail below in conjunction with the accompanying drawings and examples.

[0031] refer to figure 1 , the implementation steps of the present invention are as follows:

[0032] Step 1, obtain the event flow of the dynamic vision sensor DVS.

[0033] 1a) Build a platform for dynamic vision sensor DVS:

[0034] 1a1) Connect the dynamic vision sensor DVS to the computer, open the FrontPanelUSB-DriverOnly-4.5.5.exe file in the FPGABoard Driver folder, and follow the prompts to install the driver of the dynamic vision sensor;

[0035] 1a2) Open the dynamic visual sensor test program GUI.exe in the GUI-Release folder, if the shooting scene can be displayed in the pop-up window, it means that it can work normally;

[0036] 1a3) Install commercial Microsoft Visual Studio 2013 software on the computer, and configure Opencv3.0;

[0037] 1b) Use Microsoft Visual Studio 2013 to open DVS_record.sln in the DVS_record folder, and modify ...

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Abstract

The invention discloses a shared k-SVD dictionary-based DVS visual video denoising method. The problem that an image object generated at a high frame rate is unclear in contour and long in consumed time is mainly solved. The scheme of the method is as follows: 1, installing the drive of a dynamic video sensor, capturing an event stream and storing the event stream; 2, converting the event stream into DVS images with clear contours, and grouping the images; 3, obtaining an optimized dictionary of a first frame of image in each group according to the k-SVD algorithm, and subjecting all the restimages to denoising treatment by using a learning dictionary obtained by the first frame of image in each group; 4, setting a video frame rate and a frame number, and carrying out transcoding treatment on the DVS images after being subjected to denoising treatment. According to the invention, an object has obvious profile and other characteristics under the condition that a high frame rate is ensured. Moreover, a good denoising effect and a high denoising speed can be achieved while the structure information of the object is reserved. The method can be used for the image pretreatment of DVS development.

Description

technical field [0001] The invention belongs to the technical field of image processing, mainly relates to denoising of DVS visualized video, and can be used for image preprocessing of DVS development. Background technique [0002] At present, frame-based traditional cameras have certain limitations for capturing moving objects. Dynamic vision sensor DVS is an event-based camera, which only pays attention to the changed pixels, and has the characteristics of no frame, high speed and low bandwidth. These characteristics make DVS have very good prospect in practical application. [0003] DVS stores captured scenes in the form of events, so events can be used to visualize the scenes recorded by DVS, that is, convert the event stream into a frame-by-frame DVS visualization image, and then obtain DVS visualization video. Missing information and noise interference are two problems in the visualization process. At present, a visualization method has been proposed, which is to vi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T5/50
Inventor 谢雪梅李旺杜江石光明刘碗杨建秀
Owner XIDIAN UNIV
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