Gauss noise variance estimation method based on NSCT and PCA

A technique of Gaussian noise and variance estimation, which is applied in the field of noise estimation and can solve the problems of inaccurate noise variance estimation.

Inactive Publication Date: 2016-02-03
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 inv

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  • Gauss noise variance estimation method based on NSCT and PCA
  • Gauss noise variance estimation method based on NSCT and PCA
  • Gauss 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 Gauss noise variance estimation method based on NSCT and PCA belongs to the technical field of variance estimation. According to the method, a raw image with Gauss noise is firstly subjected to NSCT decomposition, and a low-pass filtering image and a plurality of high-pass filtering images in different directions are obtained; a new image Y is obtained by subtracting the low-pass filtering image from the raw image, and the image Y contains the Gauss noise and high-frequency information of the raw image; then an edge detection algorithm is used for edge detection of the image Y, and detected edge positions are marked; edge position images are removed, and the noise variances of non-edge position images are estimated by means of a PCA method. The method is widely applicable, more precise, and more robust.

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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IPC IPC(8): G06T5/00G06T7/00
Inventor 崔克彬牛为华袁和金
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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