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Speckle noise suppression method based on hypercomplex wavelet amplitude soft threshold

A speckle noise and hypercomplex technology, applied in the field of image processing, can solve the problem that the wavelet threshold cannot achieve the optimal effect

Inactive Publication Date: 2012-12-12
HARBIN INST OF TECH
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Problems solved by technology

[0007] The purpose of the present invention is to overcome the deficiency that the existing wavelet threshold cannot achieve the optimal effect, and to provide a soft threshold speckle noise suppression method based on super-complex wavelet transform amplitude modeling

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  • Speckle noise suppression method based on hypercomplex wavelet amplitude soft threshold
  • Speckle noise suppression method based on hypercomplex wavelet amplitude soft threshold
  • Speckle noise suppression method based on hypercomplex wavelet amplitude soft threshold

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specific Embodiment approach

[0071] Execute step 1: perform HWT on the image containing speckle noise, and obtain the super-complex wavelet coefficient represented by the real part-imaginary part.

[0072] by figure 2 For example, the image resolution is 256*256. The results after one layer of HWT are shown in Figure 3-6 .

[0073] Execute step 2: convert the result obtained in step 1 Figure 3-6 The displayed real-imaginary part representation of the hypercomplex wavelet coefficient image is converted into a magnitude-phase representation, and the magnitude component used in coefficient modeling is shown in Figure 7-10 .

[0074] Step 3: Estimate the noise threshold of the magnitude coefficient of the hypercomplex wavelet.

[0075] Because the phase component represented by the magnitude-phase of the supercomplex wavelet is less affected by noise, so only the estimation of the noise threshold for the magnitude coefficient can achieve a good denoising effect. Figure 3-6 The estimated noise thres...

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Abstract

The invention discloses a speckle noise suppression method based on a hypercomplex wavelet amplitude soft threshold and relates to an image denoising method in the field of image processing. In order to overcome the defect that the conventional wavelet threshold cannot reach an optimal effect, the speckle noise suppression method comprises the following steps of: 1, performing HWT (hypercomplex wavelet transform) on a noise image to obtain a hypercomplex wavelet coefficient; 2, converting the hypercomplex wavelet coefficient represented by a real part and an imaginary part into an amplitude-phase representation form; 3, estimating the noise threshold of the hypercomplex wavelet amplitude coefficient; 4, performing soft threshold processing on the hypercomplex wavelet amplitude coefficient according to the noise threshold; and 5, combining the processed hypercomplex wavelet amplitude coefficient and an unprocessed phase system, and performing hypercomplex wavelet inverse transformation to obtain the image denoising result. According to the method, the capacity of representing the hypercomplex wavelet phase texture can be exerted, so that the approximate optimal threshold of the noise suppression is selected; and moreover, the texture structure information of the image is kept, and an ideal image denoising result is obtained.

Description

technical field [0001] The invention relates to an image denoising method in the field of image processing, in particular to an image speckle noise suppression method based on supercomplex wavelet amplitude modeling and soft threshold. Background technique [0002] Speckle noise is a multiplicative noise that is different from additive Gaussian noise, and it exists widely in ultrasound and radar imaging. Compared with MRI and CT, ultrasound is a relatively cheap imaging mode. It is portable and can acquire images in real time. However, ultrasound is limited by the attenuation and penetration of sound waves, and the imaging resolution and contrast are low. . For further analysis, ultrasound images need to be preprocessed, including speckle noise suppression and image enhancement. [0003] Speckle noise is caused by a certain number of scatterers with random phases whose size is smaller than the resolution of the ultrasound beam. The presence of spots reduces the visual eff...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 刘义鹏金晶王强沈毅
Owner HARBIN INST OF TECH
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