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A Noise Intensity Adaptive Nonlocal Mean Image Denoising Method

A non-local mean value and noise intensity technology, which is applied in image enhancement, image data processing, instruments, etc., can solve the problem of unsatisfactory image denoising effect, achieve overcoming fixed denoising intensity parameters, improve denoising effect, and improve denoising effect. noise effect

Inactive Publication Date: 2017-08-25
XIAN UNIV OF TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide a noise intensity self-adaptive non-local mean image denoising method to solve the technical problem that the existing non-local mean denoising method uses the same denoising intensity parameter to cause unsatisfactory image denoising effect

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Embodiment Construction

[0038] The present invention will be described in detail below with reference to the drawings and specific embodiments.

[0039] The invention provides a noise intensity self-adaptive non-local mean image denoising method, which is specifically implemented according to the following steps:

[0040] Step 1: Collect the grayscale image on the KODAK Gray Scale grayscale card and input it into the computer. The grayscale image contains 20 areas with different brightness from black to white. The grayscale image is recorded as z( i), where i represents a pixel point, z represents the brightness value of the pixel point, and the brightness area is recorded as X m , 1≤m≤20;

[0041] Step 2: Obtain the optimal denoising intensity parameters under different brightness, the specific process is as follows:

[0042] Step 2.1, use the non-local mean algorithm to denoise the grayscale image z(i) using different denoising intensity parameters to obtain different brightness Y m The correspo...

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Abstract

The invention discloses a noise intensity self-adaptive non-local mean image denoising method. Firstly, the gray scale bar image is collected, and the non-local mean method is used to denoise it using different denoising intensity parameters to obtain the best image under different brightness. denoising intensity parameters; then use the linear interpolation method to calculate the optimal denoising intensity parameters corresponding to other brightness; finally use the optimal denoising intensity parameters corresponding to different brightnesses to denoise the image in the logarithmic domain, and the The image after digital domain denoising is subjected to exponential transformation to obtain the final image after denoising. The present invention overcomes the shortcomings of fixed denoising intensity parameters in the existing methods, and improves the denoising effect of the image; at the same time, processing in the logarithmic domain helps to increase the difference in pixel brightness in dark areas, reduce the difference in bright areas, and more It is beneficial to improve the denoising effect of the image.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and relates to a noise intensity self-adaptive non-local mean image denoising method. Background technique [0002] In the process of digital image acquisition, it will inevitably be interfered by various noise signals, which will degrade the image quality and affect the later image feature extraction, target segmentation and target recognition. Therefore, image denoising has important practical application value. [0003] Image denoising methods can be divided into two categories: spatial domain-based methods and transform domain-based methods. Methods based on the spatial domain include bilateral filtering and Gaussian filtering based on the gray similarity of a single pixel, and methods based on the transform domain such as various image denoising methods based on wavelet transform. The traditional spatial domain denoising method is based on single pixel information, which ca...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 张二虎李敬朱仁兵张卓敏
Owner XIAN UNIV OF TECH
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