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Method for denoising video based on surfacelet conversion characteristic

A technology of transforming characteristics and video, which is applied in the field of image processing and video processing, can solve the problems of not using the correlation of video images and effectively improving the denoising effect of video images, so as to achieve the effect of improving the denoising effect

Inactive Publication Date: 2012-07-04
XIDIAN UNIV
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Problems solved by technology

Although this method greatly reduces the computational complexity of the existing non-local mean spatial domain time-varying filtering method, it still has the disadvantage that this method only considers the correlation between pixels in the current frame, and does not take advantage of the correlation between video image frames. Correlation, cannot effectively improve the denoising effect of video images

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  • Method for denoising video based on surfacelet conversion characteristic
  • Method for denoising video based on surfacelet conversion characteristic
  • Method for denoising video based on surfacelet conversion characteristic

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Embodiment Construction

[0057] Attached below figure 1 The present invention is further described.

[0058] Step 1, input a video to be denoised, the video size is 192×192×192 pixels, and the added noise is Gaussian white noise.

[0059]Step 2, obtain the Surfacelet domain coefficients of the video to be denoised.

[0060] Call the Surfacelet toolkit to perform Surfacelet transformation on the video to be denoised, and obtain the high-frequency subband coefficients in the Surfacelet domain of the video to be denoised.

[0061] Step 3, use the noise estimation formula to estimate the noise standard deviation of the video to be denoised.

[0062] In the high-frequency subband of the Surfacelet domain of the noisy video, its energy is mainly provided by the noise. The noise in the Surfacelet domain is Gaussian white noise with independent and identical distribution, and the noise variance is constant, so Donoho proposes to use the robust median to estimate Noise standard deviation.

[0063] The nois...

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Abstract

The invention discloses a method for denoising a video based on a surfacelet conversion characteristic. The method comprises the following steps of: inputting a video to be denoised; acquiring a high-frequency sub-band coefficient; estimating a noise standard difference; acquiring the energy of a corresponding scale of the surfacelet domain of the video to be denoised; acquiring the regulating factor of the high-frequency sub-band; acquiring a basic threshold value; acquiring the regulating factor of the high-frequency sub-band coefficient; acquiring the threshold value of the high-frequency sub-band coefficient; acquiring a high-frequency sub-band coefficient of the surfacelet domain of the denoised video; and acquiring the denoised video. According to the method, a video and noise are distinguished by using the surfacelet coefficient, so that the relevance existing between the pixel and the frame of the video image is fully utilized, the noise can be effectively removed, and the edge detailed information of the video image can be better kept simultaneously.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a video denoising method based on Surfacelet transformation characteristics in the technical field of video processing. The invention can be used for the removal of video image additive noise. Background technique [0002] In the process of video image acquisition and transmission, the introduction of noise is inevitable. Since video images have great correlation between adjacent pixels and frames, while noise is random and irrelevant, this provides a theoretical basis for video image noise removal in the spatio-temporal domain. Since the noisy video image has different characteristics in the transform domain after wavelet transform and Surfacelet transform, the video image and noise have different characteristics, so denoising the video image in the transform domain can also achieve a good denoising effect. [0003] The patent application "A Video Image Noise Es...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N5/217
Inventor 田小林焦李成聂继勇张小华缑水平马文萍钟桦朱虎明
Owner XIDIAN UNIV
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