CN102592263A - Image reinforcement method based on frequency domain - Google Patents
Image reinforcement method based on frequency domain Download PDFInfo
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- CN102592263A CN102592263A CN2011100007736A CN201110000773A CN102592263A CN 102592263 A CN102592263 A CN 102592263A CN 2011100007736 A CN2011100007736 A CN 2011100007736A CN 201110000773 A CN201110000773 A CN 201110000773A CN 102592263 A CN102592263 A CN 102592263A
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Abstract
The invention relates to an image reinforcement method based on a frequency domain, relating to an image and belonging to the field of electronic information engineering. The image reinforcement method is characterized by comprising the steps of: firstly, performing frequency conversion on an image to convert the image from space into the frequency domain; and then, operating the whole image in the frequency domain, performing wave filtering processing on the image through low pass wave filtering or high pass wave filtering to reinforce a high-frequency signal on the edge; and finally, converting the processed conversion value into a space domain so as to improve the image details or the clearness of texture edges. The image reinforcement method of the invention can clear fuzzy images or emphasize concerned characteristics and inhibit unconcerned characteristics to improve the image quality, enrich the information quantity, and reinforce the image interpretation and identification effects. Meanwhile, the method is simple and the operation speed is high, so the image reinforcement method has an extensive application range.
Description
Technical field
The present invention relates to a kind of image enchancing method, relate in particular to a kind of image enchancing method based on frequency domain.
Background technology
Image enhancement technique is one type of basic image processing techniques, its objective is to make the fuzzy image sharpening or the characteristic of outstanding certain aspect, yet the traditional image enhancing is to realize through gray scale and the contrast of adjusting image, has certain limitation.Image enchancing method based on frequency domain is that image is carried out frequency domain transform, not only can make fuzzy image become clear, and can stress the characteristic of some concern, suppresses the characteristic of non-concern, strengthens image interpretation and recognition effect.Implementation method is simple simultaneously, and operating speed is fast, has broad application prospects.
Summary of the invention
The object of the invention is exactly the problems referred to above that exist in the prior art in order to solve, and a kind of image enchancing method based on frequency domain is provided.
The object of the invention is realized through following technological bill:
Image enchancing method based on frequency domain relates to image, wherein: at first image is carried out frequency transformation; Image is transformed from a spatial domain to frequency domain; In frequency domain, entire image is operated then, image is carried out Filtering Processing, strengthen the high-frequency signal at edge through LPF or high-pass filtering; Spatial domain is changed in transformed value inversion after will handling at last, thereby improves the details of image or the sharpness at texture edge.
Above-mentioned image enchancing method based on frequency domain, wherein: adopt the Fast Fourier Transform (FFT) method that image is carried out frequency domain transform, image is transformed from a spatial domain to frequency field.
Further, based on the image enchancing method of frequency domain, wherein: described Fourier transform can convert reluctant time-domain signal in the image to be easy to analyze frequency-region signal.
Further, based on the image enchancing method of frequency domain, wherein: the global information to image in frequency domain carries out the frequency domain filtering processing.
Further, based on the image enchancing method of frequency domain, wherein: described LPF can suppress or stop passing through of the interior high fdrequency component of frequency domain, makes the image border level and smooth thereby remove image noise.
Further, based on the image enchancing method of frequency domain, wherein: described high-pass filtering can strengthen high fdrequency component in the frequency domain, slacken low frequency component, and edge of image is strengthened.
Again further, based on the image enchancing method of frequency domain, wherein: described high fdrequency component is meant image edge information, picture noise.
Substantive distinguishing features and obvious improvement that technical scheme of the present invention is outstanding are embodied in: after adopting the present invention; Can make the fuzzy image characteristic of clear or emphasical some concern that becomes; The characteristic that suppresses non-concern makes it to improve picture quality, abundant information amount, strengthens image interpretation and recognition effect.Implementation method is simple simultaneously, and operating speed is fast, has broad application prospects.
The object of the invention, advantage and characteristics will be explained through following embodiment.These embodiment only are the prominent examples of using technical scheme of the present invention, and all technical schemes of taking to be equal to replacement or equivalent transformation and forming all drop within protection scope of the present invention.
Embodiment
Image enchancing method based on frequency domain relates to image, and its special feature is: at first adopt the Fast Fourier Transform (FFT) method that image is carried out frequency transformation; Image is transformed from a spatial domain to frequency domain; In frequency domain, entire image is operated then, image is carried out Filtering Processing, strengthen the high-frequency signal at edge through LPF or high-pass filtering; Spatial domain is changed in transformed value inversion after will handling at last, thereby improves the details of image or the sharpness at texture edge.
Fourier transform provides an approach of from the spatial domain to the frequency, freely changing; That is to say; Can image be transformed into frequency distribution from intensity profile; Convert reluctant time-domain signal in the image to be easy to analyze frequency-region signal (frequency spectrum of signal), utilized some instruments that these frequency-region signals are handled, processed then.
As far as image, edge of image partly is the sudden change part, changes comparatively fast, and therefore being reflected on the frequency domain is high fdrequency component, is HFS under the most of situation of the noise of image; Image smooth variation part then is a low frequency component.Adopt low pass filtering method can suppress or stop passing through of high fdrequency component, thereby remove image noise, make the image border become level and smooth; High-pass filtering method can strengthen high fdrequency component, slacken the low frequency frequency component, thereby edge of image is strengthened.
Can find out through above-mentioned text description, behind the present invention, can make the fuzzy image characteristic of clear or emphasical some concern that becomes, suppress the characteristic of non-concern, make it to improve picture quality, abundant information amount, strengthen image interpretation and recognition effect.Implementation method is simple simultaneously, and operating speed is fast, has broad application prospects.
Claims (7)
1. based on the image enchancing method of frequency domain, belong to the Electronics and Information Engineering field, it is characterized in that: at first image is carried out frequency transformation; Image is transformed from a spatial domain to frequency domain; In frequency domain, entire image is operated then, image is carried out Filtering Processing, strengthen the high-frequency signal at edge through LPF or high-pass filtering; Spatial domain is changed in transformed value inversion after will handling at last, thereby improves the details of image or the sharpness at texture edge.
2. the image enchancing method based on frequency domain according to claim 1 is characterized in that: adopt the Fast Fourier Transform (FFT) method that image is carried out frequency domain transform, image is transformed from a spatial domain to frequency field.
3. the image enchancing method based on frequency domain according to claim 2 is characterized in that: described Fourier transform can convert reluctant time-domain signal in the image to be easy to analyze frequency-region signal.
4. the image enchancing method based on frequency domain according to claim 1 is characterized in that: the global information to image in frequency domain carries out the frequency domain filtering processing.
5. the image enchancing method based on frequency domain according to claim 1 is characterized in that: described LPF can suppress or stop passing through of the interior high fdrequency component of frequency domain, makes the image border level and smooth thereby remove image noise.
6. the image enchancing method based on frequency domain according to claim 1 is characterized in that: described high-pass filtering can strengthen high fdrequency component in the frequency domain, slacken low frequency component, and edge of image is strengthened.
7. the image enchancing method based on frequency domain according to claim 6 is characterized in that: described high fdrequency component is meant image edge information, picture noise.
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Cited By (14)
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| CN104937411A (en) * | 2012-09-24 | 2015-09-23 | 布里格姆女子医院有限公司 | Portal and method for management of dialysis therapy |
| CN105139362A (en) * | 2015-09-23 | 2015-12-09 | 成都融创智谷科技有限公司 | Image enhancing method based on frequency domain |
| CN106886787A (en) * | 2017-03-07 | 2017-06-23 | 华中科技大学 | A kind of operation signal data theoretical based on two-dimensional convolution is extracted and storage method |
| CN107292275A (en) * | 2017-06-28 | 2017-10-24 | 北京飞搜科技有限公司 | Face characteristic recognition methods and system that a kind of frequency domain is divided |
| CN107644405A (en) * | 2017-09-11 | 2018-01-30 | 北京小米移动软件有限公司 | Image processing method and device, electronic equipment and computer-readable recording medium |
| CN109243010A (en) * | 2018-07-20 | 2019-01-18 | 李艳芹 | Home dwelling door lock control platform |
| CN109345501A (en) * | 2018-08-06 | 2019-02-15 | 天津普智捷信息技术有限公司 | Spiral winded type material defect inspection method based on frequency domain image enhancement |
| CN109660807A (en) * | 2017-10-10 | 2019-04-19 | 优酷网络技术（北京）有限公司 | A kind of video image code-transferring method and device |
| CN110431407A (en) * | 2019-06-20 | 2019-11-08 | 长江存储科技有限责任公司 | Polysilicon characterizing method |
| CN111242089A (en) * | 2019-09-23 | 2020-06-05 | 神盾股份有限公司 | Electronic device for removing background noise based on spatial frequency and image signal processing method |
| CN111798392A (en) * | 2020-06-29 | 2020-10-20 | 佛山科学技术学院 | Object edge noise reduction method and system for infrared image |
| CN114296443A (en) * | 2021-11-24 | 2022-04-08 | 贵州理工学院 | Unmanned modular combine harvester |
| CN115423725A (en) * | 2022-11-04 | 2022-12-02 | 北京数慧时空信息技术有限公司 | Remote sensing image restoration method and device |
| CN117422939A (en) * | 2023-12-15 | 2024-01-19 | 武汉纺织大学 | Breast tumor classification method and system based on ultrasonic feature extraction |
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104937411A (en) * | 2012-09-24 | 2015-09-23 | 布里格姆女子医院有限公司 | Portal and method for management of dialysis therapy |
| CN105139362A (en) * | 2015-09-23 | 2015-12-09 | 成都融创智谷科技有限公司 | Image enhancing method based on frequency domain |
| CN106886787A (en) * | 2017-03-07 | 2017-06-23 | 华中科技大学 | A kind of operation signal data theoretical based on two-dimensional convolution is extracted and storage method |
| CN107292275B (en) * | 2017-06-28 | 2020-04-10 | 北京飞搜科技有限公司 | Frequency domain division human face feature recognition method and system |
| CN107292275A (en) * | 2017-06-28 | 2017-10-24 | 北京飞搜科技有限公司 | Face characteristic recognition methods and system that a kind of frequency domain is divided |
| CN107644405A (en) * | 2017-09-11 | 2018-01-30 | 北京小米移动软件有限公司 | Image processing method and device, electronic equipment and computer-readable recording medium |
| CN109660807A (en) * | 2017-10-10 | 2019-04-19 | 优酷网络技术（北京）有限公司 | A kind of video image code-transferring method and device |
| CN109243010A (en) * | 2018-07-20 | 2019-01-18 | 李艳芹 | Home dwelling door lock control platform |
| CN109345501A (en) * | 2018-08-06 | 2019-02-15 | 天津普智捷信息技术有限公司 | Spiral winded type material defect inspection method based on frequency domain image enhancement |
| CN110431407A (en) * | 2019-06-20 | 2019-11-08 | 长江存储科技有限责任公司 | Polysilicon characterizing method |
| CN110431407B (en) * | 2019-06-20 | 2020-08-25 | 长江存储科技有限责任公司 | Polycrystalline silicon characterization method |
| US11467084B2 (en) | 2019-06-20 | 2022-10-11 | Yangtze Memory Technologies Co., Ltd. | Methods for polysilicon characterization |
| CN111242089A (en) * | 2019-09-23 | 2020-06-05 | 神盾股份有限公司 | Electronic device for removing background noise based on spatial frequency and image signal processing method |
| CN111798392A (en) * | 2020-06-29 | 2020-10-20 | 佛山科学技术学院 | Object edge noise reduction method and system for infrared image |
| CN114296443A (en) * | 2021-11-24 | 2022-04-08 | 贵州理工学院 | Unmanned modular combine harvester |
| CN114296443B (en) * | 2021-11-24 | 2023-09-12 | 贵州理工学院 | Unmanned modularized combine harvester |
| CN115423725A (en) * | 2022-11-04 | 2022-12-02 | 北京数慧时空信息技术有限公司 | Remote sensing image restoration method and device |
| CN117422939A (en) * | 2023-12-15 | 2024-01-19 | 武汉纺织大学 | Breast tumor classification method and system based on ultrasonic feature extraction |
| CN117422939B (en) * | 2023-12-15 | 2024-03-08 | 武汉纺织大学 | Breast tumor classification method and system based on ultrasonic feature extraction |
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Application publication date: 20120718 |