Environment self-adaptation video image de-noising method and device

A video image, adaptive technology, applied in the field of image processing, can solve the problems of moving object smear, video image edge blur, etc., achieve good noise reduction effect, solve the effect of edge blur and moving object smear

Active Publication Date: 2014-09-03
武汉众智数字技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] In view of the above problems, the purpose of the present invention is to provide an environment adaptive video image noise reduction method and device, aiming to solve the technical problems of blurred edges of video images and smearing of moving objects after noise reduction processing in existing noise reduction technologies

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  • Environment self-adaptation video image de-noising method and device
  • Environment self-adaptation video image de-noising method and device
  • Environment self-adaptation video image de-noising method and device

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Embodiment 1

[0027] figure 1 The flow of the environment adaptive video image noise reduction method provided by the embodiment of the present invention is shown, and only the parts related to the embodiment of the present invention are shown for convenience of description.

[0028] The environment adaptive video image noise reduction method provided in this embodiment includes the following steps:

[0029] Step S11 , counting the average brightness of video images under different light intensities, and determining a temporal noise reduction threshold and a spatial noise reduction threshold.

[0030] In this step, it is first necessary to determine the noise reduction level and the corresponding temporal and spatial domain noise reduction thresholds. According to the actual situation, a range of average brightness of the video image is set for each noise reduction level. During implementation, the corresponding noise reduction level and temporal and spatial noise reduction thresholds are ...

Embodiment 2

[0071] Figure 5 The flow of the environment adaptive video image noise reduction method provided by the embodiment of the present invention is shown, and only the parts related to the embodiment of the present invention are shown for convenience of description.

[0072] The environment adaptive video image noise reduction method provided in this embodiment includes the following steps:

[0073] Step S51, counting the average brightness of the video image under different light intensities, and determining the noise reduction threshold in the temporal domain and the noise reduction threshold in the spatial domain;

[0074] Step S52, acquiring noise reduction mode information, and receiving and saving the input time domain noise reduction level and spatial domain noise reduction level when the noise reduction is manual;

[0075] Step S53, when the noise reduction mode is the automatic mode, calculate the average brightness of the image according to the currently collected video...

Embodiment 3

[0080] Figure 6 The structure of the environment adaptive video image noise reduction device provided by the embodiment of the present invention is shown, and only the parts related to the embodiment of the present invention are shown for convenience of description.

[0081] The environment adaptive video image noise reduction device provided in this embodiment includes:

[0082] Threshold determination unit 61, used to count the average brightness of the video image under different light intensities, and determine the temporal domain noise reduction threshold and the spatial domain noise reduction threshold;

[0083] A noise reduction level determination unit 62, configured to calculate the average brightness of the image according to the currently collected video image, and determine the current temporal and spatial noise reduction levels according to the temporal noise reduction threshold and the spatial noise reduction threshold;

[0084] A temporal noise reduction proce...

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Abstract

The invention belongs to the technical field of image processing and provides an environment self-adaptation video image de-noising method and device. The method includes the steps that statistics is performed on the average brightness of video images under different illumination intensities, and a time domain de-noising threshold and a space domain de-noising threshold are determined; the average brightness of the images is calculated according to the currently acquired video images, and the current time domain de-noising level and the current space domain de-noising level are determined according to the time domain de-noising threshold and the space domain de-noising threshold; time domain de-noising is performed on the video images according to the time domain de-noising level; space domain de-noising is performed on the images processed through the time domain de-noising according to the space domain de-noising level. According to the environment self-adaptation video image de-noising method and device, the noise level of the video images can be evaluated by performing statistics on the illumination degree of the actual environment, time domain de-noising and space domain de-noising can be supported at the same time, de-noising can be dynamically started or stopped or the de-noising level can be adjusted according to the image noise level, and thus a good de-noising effect can be achieved, and the problems that de-noised images are fuzzy and smearing happens to moving objects are well solved.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an environment adaptive video image noise reduction method and device. Background technique [0002] The video application system mainly includes the acquisition, processing, transmission, display and other parts of video images. These processes inevitably introduce various noises. The existence of video image noise seriously affects the visual quality of video images and will affect various follow-up of video images. Processing, such as video image codec, transmission, storage, target recognition, target tracking, etc. The main noise sources of video images include: the imaging process of the camera, the transmission channel, and the circuit of the imaging system. When the image sensor is collecting images, it will be affected by the working environment and generate noise. For example, CMOS / CCD (Complementary Metal Oxide Semiconductor / Charge Coupled Device) sensors gen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N5/21
Inventor 方宏伟
Owner 武汉众智数字技术有限公司
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