Non-local mean value image denoising method based on filter window and parameter adaption

A self-adaptive, image technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as image noise and interference

Active Publication Date: 2015-10-14
INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI
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Problems solved by technology

People can intuitively obtain information from images, but due to the interference of external signals during image

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  • Non-local mean value image denoising method based on filter window and parameter adaption
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  • Non-local mean value image denoising method based on filter window and parameter adaption

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Embodiment Construction

[0046] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. This embodiment is carried out on the premise of the technical solution of the present invention, and the detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0047] Such as figure 1 As shown, the algorithm flow of this embodiment is divided into five steps: noise detection, establishment of noise calibration matrix, determination of reference point window, determination of reference point filter parameters, and weighting operation.

[0048] Step 1: Noise detection. First input the image, the present embodiment has selected 1 piece of 8-bit grayscale image peppers to carry out the denoising method of the present invention, and its size is 512 * 512 pixels, and resolution is 96 * 96DPI, as figure 2 (a) shown. Add Gaussian zero-mean noise with ...

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Abstract

The invention discloses a non-local mean value image denoising method based on a filter window and parameter adaption. According to the invention, firstly, noise is detected, and a noise calibration matrix is established according to a detection result; the size of the noise calibration matrix is consistent with the size of an image, and the matrix value at a corresponding position of each noise point is set to be 1, and the matrix value at a corresponding position of each non-noise point is set to be 0. Then, each pixel of a noise image is successively taken as a reference point, and centric to the point, a predetermined number of non-noise reference points are taken in a counterclockwise direction to be involved in computation. Finally adaptive weighting parameters are determined according to the locations of the reference points, and a weighted result is calculated and a restored pixel value is obtained; the corresponding element in the noise calibration matrix is set to be 0 and the pixel point after denoising can be used as a reference point of other noise points. Compared with traditional image denoising methods, the method provided by the invention is added with the noise detection and noise point screening, thus improving algorithm accuracy, changing a reference point selection window and improving algorithm adaptability.

Description

technical field [0001] The invention relates to an image denoising method, in particular to a nonlocal mean (Nonlocal Means, NLM) denoising method based on filter window and parameter self-adaptation, which belongs to the field of digital image preprocessing. This method realizes the effective removal of image noise, and at the same time preserves the information of the image itself as much as possible, especially the details and structure information. Through the adaptive filtering window and parameters, the applicability and intelligence of the method are enhanced, and the denoising process is simplified. It can be applied to an automatic image processing system. Background technique [0002] As the importance of information continues to increase, digital images, as an important information carrier, are widely used in all walks of life in modern society. People can intuitively obtain information from images, but due to the interference of external signals during image ac...

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Application Information

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IPC IPC(8): G06T5/00
Inventor 张栩铫刘征徐智勇杨威黄烨赖丽君吴文德
Owner INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI
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