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Noise reduction processing method and system for a noisy image

An image noise reduction and processing method technology, applied in the field of image processing, can solve the problems of improving the noise reduction effect, destroying the continuity of the image texture, and not making full use of the directionality of the Contourlet, so as to improve the quality, decompose meticulously and thoroughly, Effect of reducing noise signal

Active Publication Date: 2016-06-15
NANJING ZHONGXING SOFTWARE
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Problems solved by technology

However, the simple translation operation not only cannot make full use of the directionality of the Contourlet transformation, but also destroys the texture continuity of the image, and the improvement of the noise reduction effect is naturally limited.

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  • Noise reduction processing method and system for a noisy image
  • Noise reduction processing method and system for a noisy image
  • Noise reduction processing method and system for a noisy image

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Embodiment Construction

[0035] The present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings.

[0036] The present invention aims to provide an improved image noise reduction method and system. Firstly, the input noisy image is staggered to a certain extent, and the noisy image is sparsely decomposed in multiple scales and directions by wavelet-based Contourlet transform. And in the transform domain, the minimum Bayesian risk function is used to estimate the noise threshold of the high-frequency sub-high-frequency sub-image to denoise the threshold, and then the wavelet-based Contourlet inverse transform and the inverse mis-cut operation of the corresponding mis-cut amplitude are carried out to obtain the mis-cut The denoised image after cropping. Then repeat the previous steps, and linearly average the noise-reduced images obtained each time to obtain the final noise-reduced image to achieve the purpose of image noise reduc...

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Abstract

The invention discloses a noise-reducing processing method for a noisy image, which comprises the steps of: performing a mis-cut operation on an input noisy image to obtain a mis-cut image; using wavelet-based Contourlet transform to sparsely decompose the mis-cut image to obtain a low-frequency subsection Image and high-frequency sub-image, denoise each high-frequency sub-image to obtain denoising high-frequency sub-image; perform wavelet-based Contourlet inverse transform on low-frequency sub-image and denoising high-frequency sub-image, and then perform the same error Reverse stagger operation of cutting amplitude. The invention also discloses a noise reduction processing system for the image with noise. The invention effectively reduces the noise signal in the image, effectively retains the detailed information of the image, greatly improves the image noise reduction effect, and improves the image quality.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a noise reduction processing method and system for a noisy image. Background technique [0002] In the process of image acquisition, conversion and transmission, the image quality is easily affected by the interference of imaging equipment and external environment noise, etc. Therefore, image noise reduction is a basic and necessary preprocessing step in image engineering, and it is the key to image perception, classification and recognition. One of the key technologies. [0003] The essence of image noise reduction is pattern classification: that is, to separate the irregular "noise pattern" with point-like singularity from the regular "image pattern". Wavelet is the optimal basis for objective functions with point-like singularities, but in high-dimensional cases, wavelet analysis cannot make full use of the unique geometric characteristics of the data itself, so it i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 谭冠军车忠辉宋欣
Owner NANJING ZHONGXING SOFTWARE
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