A Gaussian Noise Variance Estimation Method Based on nsct and PCA

A technology of Gaussian noise and variance estimation, applied in the field of noise estimation, can solve the problem of inaccurate estimation of noise variance

Inactive Publication Date: 2018-02-23
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

[0003] In order to solve the technical problem of inaccurate estimation of noise variance of images containing Gaussian noise in the prior art, the present invention provides a Gaussian noise variance estimation method based on NSCT and PCA, which has universal applicability and higher precision and better robustness

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  • A Gaussian Noise Variance Estimation Method Based on nsct and PCA
  • A Gaussian Noise Variance Estimation Method Based on nsct and PCA
  • A Gaussian Noise Variance Estimation Method Based on nsct and PCA

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Embodiment Construction

[0014] In order to solve the technical problem of inaccurate estimation of noise variance of images containing Gaussian noise in the prior art, the present invention provides a Gaussian noise variance estimation method based on NSCT and PCA, which has universal applicability and higher precision and better robustness, the present invention will be further described below in conjunction with specific embodiments.

[0015] A Gaussian noise variance estimation method based on NSCT and PCA. First, an original image containing Gaussian noise is decomposed by NSCT to obtain a low-pass filtered image and multiple high-pass filtered images in different directions. Subtract A new image Y is obtained by low-pass filtering, and the image Y is an image containing Gaussian noise and high-frequency information of the original image; then, the Sobel edge detection operator is used to detect the edge information of the image Y, and these edge positions are marked, The edge detection algorithm...

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Abstract

A Gaussian noise variance estimation method based on NSCT and PCA, which belongs to the technical field of variance estimation. This method first decomposes an original image containing Gaussian noise through NSCT to obtain a low-pass filtered image and multiple images in different directions. The high-pass filter image is obtained by subtracting the low-pass filter from the original image to obtain a new image Y, which is an image containing Gaussian noise and high-frequency information of the original image; then, edge detection is performed on the image Y using the edge detection algorithm, And mark the detected edge position, remove the edge position image, and use PCA method to estimate the noise variance of other non-edge position images. This algorithm has universal applicability, higher precision and better robustness.

Description

technical field [0001] The invention belongs to the technical field of noise estimation, and relates to an estimation containing Gaussian noise variance, specifically a Gaussian noise variance estimation method based on NSCT and PCA. The algorithm has universal applicability, higher precision and better robustness. Background technique [0002] In the process of image acquisition, processing and transmission, noise is inevitable. The sources of noise include photosensitive film particles, such as scanners, digital camera sensors and circuit devices, digital equipment photon detectors, image quantization encoders and communication channels. , and most practical noise can be approximated as Gaussian noise. Denoising is an indispensable preprocessing step for most image processing applications. Gaussian noise denoising algorithms can be generally divided into two categories. One type of algorithm depends on the variance of Gaussian noise added to the image. The advantage of th...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T7/13
Inventor 崔克彬牛为华袁和金
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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