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Method for removing Poisson noise of radiation image based on shear waves

A radiation image, shear wave technology, applied in the field of image processing, can solve problems such as can not be directly generalized

Pending Publication Date: 2021-05-18
YANSHAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the wavelet transform only has limited directionality, and the edge discontinuity affects the series expansion, so its advantages cannot be directly extended to higher dimensions. The shearlet transform is very effective in providing the best sparse representation for multidimensional data. Shows advantages in image processing applications and is able to preserve detailed information

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  • Method for removing Poisson noise of radiation image based on shear waves
  • Method for removing Poisson noise of radiation image based on shear waves
  • Method for removing Poisson noise of radiation image based on shear waves

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Embodiment Construction

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0025] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application shall have the usual meanings understood by those skilled in the art to which the present invention belongs.

[0026] The present invention will be further described below in conjunction with accompanying drawing.

[0027] Such as figure 1 As shown, a method for removing Poisson noise from radiation images based on shear waves includes the following steps:

[0028] Step 1: Perform Anscombe transformation on the radiation image containing Poisson...

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Abstract

The invention discloses a method for removing Poisson noise of a radiation image based on shear waves, which aims at Poisson noise caused by statistical fluctuation of a radiation imaging system, is mainly used for medical images and large container inspection system images, and can also provide reference for other Poisson noise images. According to the method, the method comprises the steps of converting the Poisson distribution noise into approximate Gaussian distribution noise by utilizing Anscombe transformation, and decomposing noise images in multiple directions by utilizing the multi-scale and multi-resolution characteristics of shear waves to obtain high-frequency and low-frequency coefficients; removing coefficients of which the absolute values are smaller than a threshold value by using threshold value denoising, and obtaining a final Poisson noise radiation removal image through shear wave reconstruction and Anscombe correction inverse transformation. According to the method, the Poisson noise is well removed. Meanwhile, the detail information of the edge of the image can be reserved.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for removing Poisson noise from radiation images based on shear waves. Background technique [0002] Radiation imaging uses the different absorption capabilities of objects for rays, so that the internal conditions of objects can be observed, and it has a wide range of applications in medical treatment, safety inspection, and non-destructive testing. The noise of the radiation image will affect the clarity of the image, cover up the details, reduce the accuracy of human eyes and intelligent recognition, and increase the risk of misjudgment. Therefore, it is necessary to remove the noise of the radiation image. When the radiation dose is low or the scanned object is a cargo with a large mass and thickness, such as medical images and large-scale container inspection equipment scanning images, the main source of noise is statistical fluctuations, and the noise obey...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06F17/16G06F17/18
CPCG06F17/16G06F17/18G06T2207/20032G06T5/70
Inventor 王强许玉婷吴志芳战俭
Owner YANSHAN UNIV
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