Video snow noise detection method

A technology of snowflake noise and detection method, applied in television, image data processing, instruments, etc., can solve the problems of non-integrity analysis and decreased detection ability.

Active Publication Date: 2017-01-04
INESA ELECTRON +2
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AI Technical Summary

Problems solved by technology

The block mean square error detection of the preceding and following frames can effectively reduce the computing power consumption caused by distinguishing effective signals, but it is not applicable to the situation where snowflake noise has been generated in both the preceding and following frames, and when the uniformity of the snowflake noise distribution is higher and the number is larger , the detection ability decreases
Detecting difference blocks but without holistic analysis, it is easy to identify newly generated effective and complex information as snowflake noise

Method used

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Embodiment Construction

[0029] The present invention will be further described below in conjunction with specific examples.

[0030] Such as Figure 1-2 As shown, the video image acquired at any t-1 frame time of a high-definition video stream such as 1920x1080, uses this method to compress the image to 384*216 with a compression ratio of 20% using the adjacent interpolation method, and caches the t-1 frame compressed image , obtain the t-frame compressed image in the same way as above.

[0031] Differentiate the compressed image of frame t from the compressed image of frame t-1 to obtain a differential image of equal size, and replace the compressed image of frame t with the compressed image of frame t-1 for caching.

[0032] Perform Sobel operator processing on the difference map, extract the edge point map, and perform quantization processing according to the default setting that the percentage of the parameter edge point to the processing area is equal to 20%, assuming two situations:

[0033] S...

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Abstract

The invention discloses a video snow noise detection method, and belongs to the technical field of video image processing. The method comprises the following steps: 1), image preprocessing: enabling a high-resolution video image to be compressed and cached at an equal proportion after a current video image is obtained, calculating the difference of a current compressed image frame and a former compressed image frame, and obtaining a difference graph; 2), edge point extraction: carrying out the Sobel operator processing of the difference graph, obtaining an edge point result, and carrying out the quantitative analysis of the edge point result, wherein a snow noise result can be obtained under the extreme condition; 3), uniformity analysis: dividing an edge point result, which is not under the extreme condition, into N longitudinal and lateral detection zones for uniformity analysis; 4), result output: obtaining a snow noise detection result at stages of P2 or P3. The method is low in consumption of calculation power, can achieve the intervention at any moment, and is good in detection capability.

Description

technical field [0001] The invention belongs to the technical field of video image processing, in particular to a video snowflake noise detection method. Background technique [0002] In the field of video security, due to the strict requirements on the authenticity and clarity of the monitored scene, and the non-reproducible characteristics of the monitoring process, real-time diagnosis of video quality is very important. Due to factors such as the image sensor structure of the camera and the anti-interference ability of the transmission line, image noise is ubiquitous, and snowflake noise is one of the most common image noises. [0003] The filtering method is most commonly used in video image processing to reduce the impact of noise and improve image quality, but it cannot detect noise. When snowflake noise affects video quality, it cannot achieve the purpose of alarming. Image noise detection technology based on total blindness, such as wavelet detection based on two-di...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N17/00G06T7/00G06T7/40
CPCG06T2207/10016G06T2207/30168H04N17/004
Inventor 梁树宇刘玉宇王增锹赵伟吴剑清
Owner INESA ELECTRON
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