A Non-Local Mean Image Denoising Method Based on Filtering Window and Parameter Adaptation

A non-local mean and self-adaptive technology, applied in image enhancement, image data processing, instrumentation, etc., can solve image noise, interference and other problems, achieve the effect of improving the quality of denoising and avoiding excessive blur

Active Publication Date: 2017-08-11
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 acquisition and transmission, or due to the defects of the imaging system itself, image noise will inevitably form.

Method used

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  • A Non-Local Mean Image Denoising Method Based on Filtering Window and Parameter Adaptation
  • A Non-Local Mean Image Denoising Method Based on Filtering Window and Parameter Adaptation
  • A Non-Local Mean Image Denoising Method Based on Filtering Window and Parameter Adaptation

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Embodiment Construction

[0046] The embodiments of the present invention will be described in detail below in conjunction with the drawings. This embodiment is implemented on the premise of the technical solution of the present invention, and provides detailed implementation and specific operation procedures, 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 filtering parameters, and weighting operation.

[0048] Step 1: Noise detection. First input the image. In this embodiment, an 8-bit grayscale image peppers is selected to implement the denoising method of the present invention. The size is 512×512 pixels and the resolution is 96×96 DPI, such as figure 2 (a) Shown. Add Gaussian zero-mean noise with standard deviations of 18...

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Abstract

The invention discloses a non-local mean image denoising method based on filter window and parameter self-adaptation. Firstly, the noise detection is carried out, and the noise calibration matrix is ​​established according to the detection results, whose size is consistent with the image size. The matrix value corresponding to the noise point is set to 1, and the non-noise point is set to 0. Then, each pixel in the noise image is taken as a reference point in turn, and then a predetermined number of non-noise reference points are taken counterclockwise around this point to participate in the calculation. Finally, the adaptive weighting parameters are determined according to the position information of the reference point, the weighting result is calculated, and the restored pixel value is obtained, and the corresponding element of the noise calibration matrix is ​​set to 0, and the pixel point after denoising can be used as the reference point of the remaining noise points. Compared with the traditional image denoising method, this method adds noise detection and noise point screening, which improves the accuracy of the algorithm, changes the reference point selection window, and improves the adaptability of the algorithm.

Description

Technical field [0001] The present invention relates to an image denoising method, in particular to a nonlocal mean (NLM) denoising method based on filter window and parameter adaptation, belonging to the field of digital image preprocessing. This method realizes the effective removal of image noise, and at the same time preserves the image itself information as much as possible, especially the details and structure information. By adapting the filtering window and parameters, the applicability and intelligence of the method are enhanced, and the denoising process is simplified. Can be used in automated image processing systems. Background technique [0002] With the increasing importance of information, as an important information carrier, digital images are widely used in all walks of life in modern society. People can obtain information intuitively from images, but due to interference from external signals during image acquisition and transmission, or due to defects of the i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
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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