Image de-noise process of multi-template mixed filtering

A multi-template, image noise technology, applied in the field of image denoising, can solve the problems of insufficient filtering strength, complex filtering, and image smoothing effect not as good as average filtering, etc., to achieve the effect of short running time, simple calculation, and favorable hardware implementation

Inactive Publication Date: 2007-09-26
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Problems solved by technology

However, as an adaptive mean or median filter, they cannot comprehensively utilize the characteristics of the median filter and the mean filter.
Mean filtering and median filtering have their own advantages and disadvantages: mean filtering can effectively smooth the image and improve image correlation, but it is easy to blur the edges and details and cannot preserve the image structure
Median filtering can effectively remove noise and retain image details, but the image smoothing effect is not as good as mean filtering. In addition, the calculation of filtering coefficients is complicated, and the adjustment of filtering strength is

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  • Image de-noise process of multi-template mixed filtering
  • Image de-noise process of multi-template mixed filtering
  • Image de-noise process of multi-template mixed filtering

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[0037] The image denoising method based on multi-template hybrid filtering of the present invention will be described below with reference to the accompanying drawings and specific embodiments.

[0038] As shown in Figure 7, in this embodiment, the denoising processing of ground remote sensing images is taken as an example to illustrate the specific implementation steps of image denoising:

[0039] Step 1. Divide the image to be denoised into non-overlapping blocks of M×N size, so that each pixel of the image is in a certain block, except for the image edge. In this embodiment, the size of the image division block is chosen to be between 8 and 16 in length and width, which should not be too large or too small. If the blocks divided by the image are too large, the uniform areas included are less, and the denoising effect is not good. If the blocks divided by the image are too small, the regional probability and statistics will be poor and the randomness will be strong. Altern...

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Abstract

The disclosed picture removing-noise method based on multi-template mixed filter comprises: dividing the objective picture into MXN blocks without superposition to contain every pixel in some block; defining one group of filters including the mean filter and mid-value filter, every with different removing-noise strength; defining a numerical sequence with number standing for picture information size; obtaining the noise variance of the picture, calculating the uniformity level for the picture block to thereby select one filter for finishing the removing-noise. This invention simplifies calculation, and reduces real running time.

Description

technical field [0001] The invention relates to digital image processing, in particular to an image denoising method in digital image processing. Background of the invention [0002] The existence of noise causes the image to be distorted to a certain extent. If there is too much noise, it will hinder the use of the image. At this time, the image must be denoised. The process of image denoising will inevitably cause the loss of details of the original image, so noise suppression and detail preservation are a pair of contradictions, and various denoising methods must choose a balance point between the two. Existing denoising methods have their own advantages and disadvantages, and which method to choose for denoising depends on the requirements of specific applications and the characteristics of the data used. [0003] Denoising methods can be divided into spatial domain and frequency domain according to their working domain. The existing spatial domain adaptive denoising m...

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Application Information

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IPC IPC(8): H04N5/213H04N5/21H04N5/14
Inventor 王锡贵李鹏韩冀中韩承德
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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