CN107886489A - The method that medical image quality is improved based on shearing wave conversion and guiding filtering technology - Google Patents
The method that medical image quality is improved based on shearing wave conversion and guiding filtering technology Download PDFInfo
- Publication number
- CN107886489A CN107886489A CN201711262879.7A CN201711262879A CN107886489A CN 107886489 A CN107886489 A CN 107886489A CN 201711262879 A CN201711262879 A CN 201711262879A CN 107886489 A CN107886489 A CN 107886489A
- Authority
- CN
- China
- Prior art keywords
- frequency sub
- band
- filtering
- shearing wave
- medical image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001914 filtration Methods 0.000 title claims abstract description 49
- 238000006243 chemical reaction Methods 0.000 title claims abstract description 25
- 238000010008 shearing Methods 0.000 title claims abstract description 24
- 238000000034 method Methods 0.000 title claims abstract description 20
- 230000009466 transformation Effects 0.000 claims abstract description 4
- 230000002708 enhancing effect Effects 0.000 claims description 4
- 230000036039 immunity Effects 0.000 abstract description 4
- 238000005728 strengthening Methods 0.000 abstract description 2
- 230000008859 change Effects 0.000 description 3
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 1
- 230000009931 harmful effect Effects 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000002560 therapeutic procedure Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/10—Image enhancement or restoration using non-spatial domain filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
- Apparatus For Radiation Diagnosis (AREA)
Abstract
The invention discloses a kind of method for improving medical image quality based on shearing wave conversion and guiding filtering technology, comprise the following steps:Step S1, medical image is decomposed using shearing wave conversion, so as to obtain low frequency sub-band and high-frequency sub-band;Step S2, PM filtering is carried out to low frequency sub-band obtained above;Denoising is carried out to high-frequency sub-band obtained above, filtering then is guided to the high-frequency sub-band after denoising;Step S3, shearing wave inverse transformation is carried out to the low frequency sub-band by PM filtering and the high-frequency sub-band Jing Guo guiding filtering.Reach the purpose for the noise immunity for improving image definition and strengthening image.
Description
Technical field
The present invention relates to field of medical image processing, in particular it relates to a kind of based on shearing wave conversion and guiding filtering skill
The method that art improves medical image quality.
Background technology
The quality of medical image has critically important influence to doctor in diagnosis and therapeutic process.In the collection of medical image
In transmitting procedure, image can be disturbed by various factors causes image quality decrease, and follow-up processing and application are produced
Raw harmful effect.Key link of the image enhaucament as image preprocessing, there is critically important application value.
At present, image enhaucament is divided into two major classes:Spatial domain changes and frequency-domain transform.Enhancement Method based on spatial domain is directly right
The whole pixel value of image is handled, although improving the overall brightness of image, reduces the contrast of image, enlarged drawing
Noise as in, has flooded details.Spatial transform has:Histogram equalization, multiple dimensioned Retinex etc..Wavelet transformation is classical
One of algorithm, there is the characteristics of good time domain specification and multiresolution, but it can not express directional information well.In order to gram
The shortcomings that taking the limited directionality of small echo, it is proposed that much multi-scale transforms based on small echo, such as:Qu Bo (curvelet) becomes
Change, profile ripple (contourlet) conversion and shearing wave (Shearlet) conversion.Shearlet is converted and contourlet conversion
With similar decomposable process.Both of which can realize best approximation and multiresolution analysis.
In summary:The problem of image noise immunity is not strong, and definition is not high in the prior art be present.
The content of the invention
It is an object of the present invention in view of the above-mentioned problems, propose that one kind is carried based on shearing wave conversion and guiding filtering technology
The method of high medical image quality, the advantages of improving image definition with realization and strengthen the noise immunity of image.
To achieve the above object, the technical solution adopted by the present invention is:
A kind of method for improving medical image quality based on shearing wave conversion and guiding filtering technology, comprises the following steps:
Step S1, medical image is decomposed using shearing wave conversion, so as to obtain low frequency sub-band and high-frequency sub-band;
Step S2, PM filtering is carried out to low frequency sub-band obtained above;Denoising is carried out to high-frequency sub-band obtained above, so
Filtering is guided to the high-frequency sub-band after denoising afterwards;
Step S3, shearing wave inversion is carried out to the low frequency sub-band by PM filtering and the high-frequency sub-band Jing Guo guiding filtering
Change.
Preferably, low frequency sub-band obtained above is carried out in PM filtering, the iterations that PM filtering is chosen is 2 times.
Preferably, above-mentioned steps S2 is carried out in denoising to high-frequency sub-band obtained above, and denoising uses cycle threshold method.
Preferably, the formula of the guiding filtering is specific as follows:
EI=ε (P-Q)+Q,
Wherein P is image to be filtered, and Q is that filtered image is smoothed image, and ε is enhancing parameter, and EI represents guiding filtering
Function.
Preferably, ε=2.2.
Technical scheme has the advantages that:
Technical scheme, PM is filtered and is used for high-frequency sub-band for low frequency sub-band, guiding filtering, proposes a kind of base
In the medical image new method of shearing wave conversion.By to shear wave conversion threshold value processing, to the noise that filters out of big degree, then
Channeled filtering, strengthen the detailed information of image, so as to reach the noise immunity for improving image definition and strengthening image
Purpose.
Below by drawings and examples, technical scheme is described in further detail.
Brief description of the drawings
Fig. 1 is to improve medical image quality based on shearing wave conversion and guiding filtering technology described in the embodiment of the present invention
Method obtains flow chart.
Embodiment
The preferred embodiments of the present invention are illustrated below in conjunction with accompanying drawing, it will be appreciated that described herein preferred real
Apply example to be merely to illustrate and explain the present invention, be not intended to limit the present invention.
As shown in figure 1,
A kind of method for improving medical image quality based on shearing wave conversion and guiding filtering technology, comprises the following steps:
Step S1, medical image is decomposed using shearing wave conversion, so as to obtain low frequency sub-band and high-frequency sub-band;
Step S2, PM filtering is carried out to low frequency sub-band obtained above;Denoising is carried out to high-frequency sub-band obtained above, so
Filtering is guided to the high-frequency sub-band after denoising afterwards;
Step S3, shearing wave inversion is carried out to the low frequency sub-band by PM filtering and the high-frequency sub-band Jing Guo guiding filtering
Change.
In preferred embodiment, low frequency sub-band obtained above is carried out in PM filtering, the iterations that PM filtering is chosen
For 2 times.
In preferred embodiment, above-mentioned steps S2 is carried out in denoising to high-frequency sub-band obtained above, and denoising is using circulation
Threshold method.
Image guiding filtering is a kind of local linear image filter, can also be had while it realizes smothing filtering good
Good edge retention energy.Filtering includes image Q after navigational figure I, pending image P and processing.Wherein I and P is can
With identical, the two is all gray level image.The key of guiding filtering is in office for navigational figure I and pending image P
The hypothesis of portion's linear relationship.Centered on pixel k, r is the square local window w of radiuskIn, P is I linear transformation, i.e.,:
A in formulak,bkIt is the coefficient of conversion, in local window wkIn be constant value.(a is constant coefficient), this
Local Linear Model ensures that filtering output image and navigational figure keep identical marginality, so this filtered image border
Keep fine.
The enhancing of guiding filtering is as follows:
I.e. in preferred embodiment, the formula of guiding filtering is specific as follows:
EI=ε (P-Q)+Q,
Wherein P is image to be filtered, and Q is that filtered image is smoothed image, and ε is enhancing parameter, and EI represents guiding filtering
Function.The size of ε values determines the definition of detail section, but also has an impact simultaneously to noise.Therefore ε value is critically important.
In preferred embodiment, ε=2.2.
Shearlet conversion mathematic(al) structures are simple, have higher computational efficiency.Shearing wave conversion has nonlinearity erron
Degree of approximation, successively segmented in frequency space, can preferably represent performance.
In summary, it is of the invention
Finally it should be noted that:The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention,
Although the present invention is described in detail with reference to the foregoing embodiments, for those skilled in the art, it still may be used
To be modified to the technical scheme described in foregoing embodiments, or equivalent substitution is carried out to which part technical characteristic.
Within the spirit and principles of the invention, any modification, equivalent substitution and improvements made etc., it should be included in the present invention's
Within protection domain.
Claims (5)
- A kind of 1. method that medical image quality is improved based on shearing wave conversion and guiding filtering technology, it is characterised in that including Following steps:Step S1, medical image is decomposed using shearing wave conversion, so as to obtain low frequency sub-band and high-frequency sub-band;Step S2, PM filtering is carried out to low frequency sub-band obtained above;Denoising is carried out to high-frequency sub-band obtained above, it is then right High-frequency sub-band after denoising guides filtering;Step S3, shearing wave inverse transformation is carried out to the low frequency sub-band by PM filtering and the high-frequency sub-band Jing Guo guiding filtering.
- 2. the method according to claim 1 that medical image quality is improved based on shearing wave conversion and guiding filtering technology, Characterized in that, being carried out to low frequency sub-band obtained above in PM filtering, the iterations that PM filtering is chosen is 2 times.
- 3. the method according to claim 1 that medical image quality is improved based on shearing wave conversion and guiding filtering technology, Characterized in that, above-mentioned steps S2 is carried out in denoising to high-frequency sub-band obtained above, denoising uses cycle threshold method.
- 4. the method according to claim 1 that medical image quality is improved based on shearing wave conversion and guiding filtering technology, Characterized in that, the formula of the guiding filtering is specific as follows:EI=ε (P-Q)+Q,Wherein P is image to be filtered, and Q is that filtered image is smoothed image, and ε is enhancing parameter, and EI represents guiding filtering function.
- 5. the method according to claim 4 that medical image quality is improved based on shearing wave conversion and guiding filtering technology, Characterized in that, ε=2.2.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711262879.7A CN107886489A (en) | 2017-12-04 | 2017-12-04 | The method that medical image quality is improved based on shearing wave conversion and guiding filtering technology |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711262879.7A CN107886489A (en) | 2017-12-04 | 2017-12-04 | The method that medical image quality is improved based on shearing wave conversion and guiding filtering technology |
Publications (1)
Publication Number | Publication Date |
---|---|
CN107886489A true CN107886489A (en) | 2018-04-06 |
Family
ID=61773091
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201711262879.7A Pending CN107886489A (en) | 2017-12-04 | 2017-12-04 | The method that medical image quality is improved based on shearing wave conversion and guiding filtering technology |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN107886489A (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108230279A (en) * | 2018-04-08 | 2018-06-29 | 新疆大学 | The medical image enhancement method being combined based on shearing wave conversion with fuzzy contrast |
CN109191416A (en) * | 2018-08-29 | 2019-01-11 | 西安电子科技大学 | Image interfusion method based on sparse dictionary study and shearing wave |
CN109584322A (en) * | 2018-10-10 | 2019-04-05 | 浙江工业大学 | Based on the smooth Shearlet medicine PET image denoising method of frequency domain direction |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106157261A (en) * | 2016-06-23 | 2016-11-23 | 浙江工业大学之江学院 | The shearler of translation invariance converts Medical Image Denoising method |
CN106846288A (en) * | 2017-01-17 | 2017-06-13 | 中北大学 | A kind of many algorithm fusion methods of bimodal infrared image difference characteristic Index |
-
2017
- 2017-12-04 CN CN201711262879.7A patent/CN107886489A/en active Pending
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106157261A (en) * | 2016-06-23 | 2016-11-23 | 浙江工业大学之江学院 | The shearler of translation invariance converts Medical Image Denoising method |
CN106846288A (en) * | 2017-01-17 | 2017-06-13 | 中北大学 | A kind of many algorithm fusion methods of bimodal infrared image difference characteristic Index |
Non-Patent Citations (3)
Title |
---|
DEEP GUPTA ET AL: "Despeckling of ultrasound medical images using nonlinear adaptive anisotropic diffusion in nonsubsampled shearlet domain", 《BIOMEDICAL SIGNAL PROCESSING AND CONTROL》 * |
何旭: "基于多尺度几何分析和各向异性扩散的医学超声图像去噪算法研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
吕笃良 等: "基于非下采样剪切波变换与引导滤波结合的遥感图像增强", 《计算机应用》 * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108230279A (en) * | 2018-04-08 | 2018-06-29 | 新疆大学 | The medical image enhancement method being combined based on shearing wave conversion with fuzzy contrast |
CN109191416A (en) * | 2018-08-29 | 2019-01-11 | 西安电子科技大学 | Image interfusion method based on sparse dictionary study and shearing wave |
CN109584322A (en) * | 2018-10-10 | 2019-04-05 | 浙江工业大学 | Based on the smooth Shearlet medicine PET image denoising method of frequency domain direction |
CN109584322B (en) * | 2018-10-10 | 2023-12-26 | 四川省工程装备设计研究院有限责任公司 | Shearlet medical PET image denoising method based on frequency domain direction smoothing |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Yang et al. | Medical image enhancement algorithm based on wavelet transform | |
CN100550978C (en) | A kind of self-adapting method for filtering image that keeps the edge | |
CN108921800A (en) | Non-local mean denoising method based on form adaptive search window | |
CN107610074A (en) | A kind of method for improving Remote Sensing Image Quality | |
CN104616255B (en) | Self-adapting enhancement method based on mammography X | |
CN107886489A (en) | The method that medical image quality is improved based on shearing wave conversion and guiding filtering technology | |
CN110211058A (en) | A kind of data enhancement methods of medical image | |
CN108389163A (en) | A kind of self-adapting enhancement method based on half-light coloured image | |
CN106875353B (en) | The processing method and processing system of ultrasound image | |
CN104715461A (en) | Image noise reduction method | |
CN104182939B (en) | Medical image detail enhancement method | |
CN107464226A (en) | A kind of image de-noising method based on improvement two-dimensional empirical mode decomposition algorithm | |
CN105184743A (en) | Image enhancement method based on non-linear guiding filtering | |
Xu et al. | A denoising algorithm via wiener filtering in the shearlet domain | |
Qing | A fractional differential approach to low contrast image enhancement | |
CN106067164B (en) | Color image contrast enhancement algorithms based on the processing of adaptive wavelet domain | |
CN111192204A (en) | Image enhancement method, system and computer readable storage medium | |
Liu et al. | Research and analysis of deep learning image enhancement algorithm based on fractional differential | |
CN101655973A (en) | Image enhancing method based on visual characteristics of human eyes | |
CN104766278A (en) | Anisotropism filtering method based on self-adaptive averaging factor | |
CN109064413B (en) | Image contrast enhancement method and image acquisition medical equipment adopting same | |
CN102081790B (en) | Noise image enhancing method based on non-linear Curvelet diffusion | |
CN105118043A (en) | Tobacco field remote sensing image enhancement algorithm | |
CN105023257B (en) | Image de-noising method based on N Smoothlets | |
CN102289793B (en) | Cyber foraging-oriented multi-scale image processing method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180406 |