Image denoising method based on Treelet switch and Gaussian scale mixture model

A Gaussian scale mixture and model technology, which is applied in the field of image processing and can solve the problems of image over-smoothing, poor detail information, blurred or filtered image structure information, etc.

Inactive Publication Date: 2012-09-12
XIDIAN UNIV
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Problems solved by technology

This method can improve the denoising effect in the case of high noise, but the disadvantage of this method is that it does not keep the detailed information in the image well, and the image after denoising is too smooth, resulting in the processed image structure information (edge, texture, point, etc.) ) are blurred or filtered out

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  • Image denoising method based on Treelet switch and Gaussian scale mixture model
  • Image denoising method based on Treelet switch and Gaussian scale mixture model
  • Image denoising method based on Treelet switch and Gaussian scale mixture model

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Embodiment Construction

[0072] Attached below figure 1 The steps of the present invention are further described in detail.

[0073] Step 1, input an image to be denoised.

[0074] Step 2, classify image blocks.

[0075] 2a) In the image to be denoised, take any pixel as the center and take a fixed length as the side length to determine a square image block, and use the same method to perform the same operation on all pixels in the image. In the embodiment of the present invention Select an image block of size 7×7.

[0076] 2b) From all image blocks selected in the image, q image block grayscale matrices are randomly selected as clustering centers, and the value of q in the embodiment of the present invention is 70.

[0077] 2c) Calculate the distance d(y) from the image block to all cluster centers according to the formula p , m k ):

[0078] d ( y p , m k ...

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Abstract

The invention discloses an image denoising method based on Treelet switch and Gaussian scale mixture model, the method solves mainly the problem of poor denoising effect on a natural image corroded by white Gaussian noise in a prior denoising method. The enforcing steps are as follows: (1) inputting an image requiring to be denoised; (2) sorting image blocks; (3) forming an array; (4) obtaining a basis array; (5) projecting; (6) estimating no-noise coefficient; (7) computing image block array after denoising; (8) estimating whether all image blocks in the image are disposed, if it is processed, step (9) is proceeded; if isn't, step (3) is proceeded; (9) normalizing all image block, and outputting the result. The image denoising method has the advantages of excellent denoising effect on the natural image corroded by white Gaussian noise and can recover intrinsic characteristic of image. The method is used for image division, target recognition, switch test and other pretreatment for image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a denoising method of Treelet transform and Gaussian scale mixture model of natural images. This method can be used for digital image preprocessing in fields such as forest resource investigation, disaster assessment, urban planning, medical imaging, and astronomical imaging. Background technique [0002] Due to the limitation of various conditions, the image will be affected by the noise in the process of acquisition, encoding, and transmission, which brings disadvantages to other subsequent processing tasks such as image segmentation, target recognition, etc., so try to recover from the noise image. Noisy images are necessary. Image denoising solves the problem of image quality degradation due to noise interference, suppresses the influence of noise, and improves image quality. It is a very important basic problem in image processing and computer vision. [000...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 王桂婷焦李成张林刚公茂果钟桦张小华田小林侯彪王爽
Owner XIDIAN UNIV
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