CN106570850A - Image fusion method - Google Patents
Image fusion method Download PDFInfo
- Publication number
- CN106570850A CN106570850A CN201610889578.6A CN201610889578A CN106570850A CN 106570850 A CN106570850 A CN 106570850A CN 201610889578 A CN201610889578 A CN 201610889578A CN 106570850 A CN106570850 A CN 106570850A
- Authority
- CN
- China
- Prior art keywords
- image
- algorithm
- rgb
- mono
- images
- 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.)
- Granted
Links
- 238000007500 overflow downdraw method Methods 0.000 title abstract 2
- 230000004927 fusion Effects 0.000 claims abstract description 13
- 238000001914 filtration Methods 0.000 claims abstract description 12
- 238000003708 edge detection Methods 0.000 claims abstract description 7
- 230000009977 dual effect Effects 0.000 claims abstract description 5
- 238000000034 method Methods 0.000 claims description 18
- 230000002146 bilateral effect Effects 0.000 claims description 6
- 238000004040 coloring Methods 0.000 claims description 3
- 235000015170 shellfish Nutrition 0.000 claims 1
- 238000000605 extraction Methods 0.000 abstract 1
- 230000000694 effects Effects 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 238000002844 melting Methods 0.000 description 1
- 230000008018 melting Effects 0.000 description 1
- 238000005457 optimization 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
- G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
-
- 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
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
-
- 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
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
- Color Television Image Signal Generators (AREA)
- Studio Devices (AREA)
Abstract
The invention discloses an image fusion method. An RGB image and an MONO image that are taken via dual cameras in a night scene mode are subjected to image fusion operation; the RGB image and the MONO image are input, the RGB image is converted into a YUV format, brightness information of the RGB image in the YUV format is separated from the same and put in an image Y1, color information is separated from the RGB image and put in an image UV1, UV1 is subjected to wave filtering operation via a wave filtering algorithm, color noise in UV1 is removed, a new image UV2 is obtained, the MONO image is subjected to de-noising operation via a de-noising algorithm, an image Y2 is obtained, Y1 is subjected to edge extraction operation via an edge detection algorithm, a new image Y3 is obtained, an image Y4 is obtained after Y2 is superposed on Y3, and a result image is obtained after Y4 and UV2 are fused. After color noise and white noise in the fused image are removed, brightness information of MONO and RGB is used, and good detail information can be obtained while the fused image is high in noise level.
Description
Technical field
The present invention relates to image processing field, particularly a kind of image interfusion method.
Background technology
With the fast development of mobile phone camera function in recent years, consumer to possess more power camera demand gradually
Rise.The photographed scene that night scene is commonly used as user, its effect optimization can effectively lift the Consumer's Experience taken pictures to camera.
Night scene shooting style at present commonly used in the trade is：Using a colour imagery shot (RGB)+black and white photographic head (MONO), by melting
Close two camera images to lift Night Scenery Effect.
In night scene is taken pictures, the brightness of MONO photographic head, details, noise can be better than RGB photographic head, therefore fusion process
In, color is provided using RGB photographic head, MONO photographic head provides brightness, details etc., calm to synthesize brightness, a details and make an uproar
All good than the RGB photographic head original image result picture of sound.But in suc scheme, the luminance detail of RGB image is just complete
Abandon, this causes fusion image, do not make full use of dual camera（RGB+MONO）All the elements.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, there is provided a kind of image interfusion method, the method is at the same time
In the case of removing fusion image chromatic noise and white noise, while using the monochrome information of MONO and RGB so that fusion image
In the case where noise level is very high, possess more preferable detailed information, so as to obtain the more preferable effect of night scene mode.
The purpose of the present invention is achieved through the following technical solutions：A kind of image interfusion method, in night scene mode
The RGB image and MONO images that lower dual camera shoots carries out image co-registration, obtains that brightness, details quality be higher and noise reduction
More preferable panoramic picture, described image interfusion method comprise the steps,
S1：Input RGB image and MONO images；
S2：RGB image is converted to into yuv format；
S3：The monochrome information of RGB image of yuv format is separated to image Y1, the colouring information of the RGB image of yuv format is separated
To image UV1；
S4：UV1 is filtered using filtering algorithm, the coloured silk removed in UV1 is made an uproar, obtains new image UV2；
S5：Denoising is carried out to MONO images using Denoising Algorithm, image Y2 is obtained；
S6：Edge extracting is done to Y1 using edge detection algorithm, new images Y3 is obtained；
S7：Y2 and Y3 are overlapped and obtain image Y4；
S8：Y4 and UV2 is carried out into fusion and obtains result images.
Described Denoising Algorithm is bilateral filtering algorithm.
The filter radius of described bilateral filtering algorithm are greatly to the journey for allowing UV1 to paste in the case where edge is kept
Degree.
Described Denoising Algorithm is NLM Denoising Algorithms.
Described edge detection algorithm is Sobel Operator, i.e. Sobel operators.
The invention has the beneficial effects as follows：The invention provides a kind of image interfusion method, the method removes fusion at the same time
In the case of Image color noise and white noise, while having used the monochrome information of MONO and RGB so that fusion image is in noise
In the case that level is very high, possess more preferable detailed information, so as to obtain the more preferable effect of night scene mode.
Description of the drawings
Fig. 1 is method of the present invention flow chart.
Specific embodiment
Technical scheme is described in further detail below in conjunction with the accompanying drawings, but protection scope of the present invention is not limited to
Described below.
A kind of image interfusion method, the RGB image and MONO images shot to dual camera in the night mode carry out figure
As fusion, obtain that brightness, details quality be higher and the more preferable panoramic picture of noise reduction, described image interfusion method include as
Lower step,
S1：Input RGB image and MONO images；
S2：RGB image is converted to into yuv format；
S3：The monochrome information of RGB image of yuv format is separated to image Y1, the colouring information of the RGB image of yuv format is separated
To image UV1；
S4：UV1 is filtered using filtering algorithm, the coloured silk removed in UV1 is made an uproar, obtains new image UV2；
S5：Denoising is carried out to MONO images using Denoising Algorithm, image Y2 is obtained；
S6：Edge extracting is done to Y1 using edge detection algorithm, new images Y3 is obtained；
S7：Y2 and Y3 are overlapped and obtain image Y4；
S8：Y4 and UV2 is carried out into fusion and obtains result images.
Described Denoising Algorithm is bilateral filtering algorithm.
The filter radius of described bilateral filtering algorithm are greatly to the journey for allowing UV1 to paste in the case where edge is kept
Degree.
Described Denoising Algorithm is NLM Denoising Algorithms.
Described edge detection algorithm is Sobel Operator, i.e. Sobel operators.
In the case that the method for the present invention removes fusion image chromatic noise and white noise at the same time, while having used MONO
With the monochrome information of RGB so that fusion image possesses more preferable detailed information in the case where noise level is very high, so as to
The more preferable effect of night scene mode is arrived.
Claims (5)
1. a kind of image interfusion method, carries out image to the RGB image and MONO images of the shooting of dual camera in the night mode
Fusion, obtains that brightness, details quality be higher and the more preferable panoramic picture of noise reduction, it is characterised in that：Described image co-registration
Method comprises the steps,
S1：Input RGB image and MONO images；
S2：RGB image is converted to into yuv format；
S3：The monochrome information of RGB image of yuv format is separated to image Y1, the colouring information of the RGB image of yuv format is separated
To image UV1；
S4：UV1 is filtered using filtering algorithm, the coloured silk removed in UV1 is made an uproar, obtains new image UV2；
S5：Denoising is carried out to MONO images using Denoising Algorithm, image Y2 is obtained；
S6：Edge extracting is done to Y1 using edge detection algorithm, new images Y3 is obtained；
S7：Y2 and Y3 are overlapped and obtain image Y4；
S8：Y4 and UV2 is carried out into fusion and obtains result images.
2. a kind of image interfusion method according to claim 1, it is characterised in that：Described Denoising Algorithm is bilateral filtering
Algorithm.
3. a kind of image interfusion method according to claim 1, it is characterised in that：The filtering of described bilateral filtering algorithm
Radius is greatly to the degree for allowing UV1 to paste in the case where edge is kept.
4. a kind of image interfusion method according to claim 1, it is characterised in that：Described Denoising Algorithm is NLM denoisings
Algorithm.
5. a kind of image interfusion method according to claim 1, it is characterised in that：Described edge detection algorithm is rope shellfish
That operator, i.e. Sobel operators.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610889578.6A CN106570850B (en) | 2016-10-12 | 2016-10-12 | A kind of image interfusion method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610889578.6A CN106570850B (en) | 2016-10-12 | 2016-10-12 | A kind of image interfusion method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106570850A true CN106570850A (en) | 2017-04-19 |
| CN106570850B CN106570850B (en) | 2019-06-04 |
Family
ID=58532806
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610889578.6A Active CN106570850B (en) | 2016-10-12 | 2016-10-12 | A kind of image interfusion method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106570850B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107770509A (en) * | 2017-10-25 | 2018-03-06 | 上海觉感视觉科技有限公司 | Pass through the method and device of YUV channel transfer MONO format-patterns |
| CN108389165A (en) * | 2018-02-02 | 2018-08-10 | 成都西纬科技有限公司 | A kind of image de-noising method |
| CN109544490A (en) * | 2018-10-17 | 2019-03-29 | 北京达佳互联信息技术有限公司 | Image enchancing method, device and computer readable storage medium |
| CN110958382A (en) * | 2018-09-26 | 2020-04-03 | 佳能株式会社 | Image processing method, image processing apparatus, imaging apparatus, and storage medium |
| CN111095919A (en) * | 2019-12-17 | 2020-05-01 | 威创集团股份有限公司 | Video fusion method and device and storage medium |
| WO2022133749A1 (en) * | 2020-12-22 | 2022-06-30 | Oppo广东移动通信有限公司 | Image processing method and apparatus, storage medium and electronic device |
| WO2022217525A1 (en) * | 2021-04-15 | 2022-10-20 | 深圳市大疆创新科技有限公司 | Image noise reduction processing method and device, and imaging device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101493893A (en) * | 2008-12-11 | 2009-07-29 | 中山大学 | Image data fusing method |
| CN102231206A (en) * | 2011-07-14 | 2011-11-02 | 浙江理工大学 | Colorized night vision image brightness enhancement method applicable to automotive assisted driving system |
| CN102298769A (en) * | 2011-06-11 | 2011-12-28 | 浙江理工大学 | Colored fusion method of night vision low-light image and infrared image based on color transmission |
| CN103595982A (en) * | 2013-11-07 | 2014-02-19 | 天津大学 | Color image collection device based on gray level sensor and color image sensor |
| WO2014187917A1 (en) * | 2013-05-23 | 2014-11-27 | bioMérieux | Method, system and computer program product for improving the quality of an image |
| CN105049718A (en) * | 2015-07-06 | 2015-11-11 | 深圳市金立通信设备有限公司 | Image processing method and terminal |
-
2016
- 2016-10-12 CN CN201610889578.6A patent/CN106570850B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101493893A (en) * | 2008-12-11 | 2009-07-29 | 中山大学 | Image data fusing method |
| CN102298769A (en) * | 2011-06-11 | 2011-12-28 | 浙江理工大学 | Colored fusion method of night vision low-light image and infrared image based on color transmission |
| CN102231206A (en) * | 2011-07-14 | 2011-11-02 | 浙江理工大学 | Colorized night vision image brightness enhancement method applicable to automotive assisted driving system |
| WO2014187917A1 (en) * | 2013-05-23 | 2014-11-27 | bioMérieux | Method, system and computer program product for improving the quality of an image |
| CN103595982A (en) * | 2013-11-07 | 2014-02-19 | 天津大学 | Color image collection device based on gray level sensor and color image sensor |
| CN105049718A (en) * | 2015-07-06 | 2015-11-11 | 深圳市金立通信设备有限公司 | Image processing method and terminal |
Non-Patent Citations (2)
| Title |
|---|
| 徐领章 等: "一种边缘优化的红外与可见光图像模块化融合方法", 《云南师范大学学报（自然科学版）》 * |
| 王健 等: "基于YUV与小波变换的可见光与红外图像融合", 《西安工业大学学报》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107770509A (en) * | 2017-10-25 | 2018-03-06 | 上海觉感视觉科技有限公司 | Pass through the method and device of YUV channel transfer MONO format-patterns |
| CN108389165A (en) * | 2018-02-02 | 2018-08-10 | 成都西纬科技有限公司 | A kind of image de-noising method |
| CN110958382A (en) * | 2018-09-26 | 2020-04-03 | 佳能株式会社 | Image processing method, image processing apparatus, imaging apparatus, and storage medium |
| US11080832B2 (en) | 2018-09-26 | 2021-08-03 | Canon Kabushiki Kaisha | Image processing method, image processing apparatus, imaging apparatus, and storage medium |
| CN109544490A (en) * | 2018-10-17 | 2019-03-29 | 北京达佳互联信息技术有限公司 | Image enchancing method, device and computer readable storage medium |
| CN109544490B (en) * | 2018-10-17 | 2021-07-13 | 北京达佳互联信息技术有限公司 | Image enhancement method, device and computer readable storage medium |
| CN111095919A (en) * | 2019-12-17 | 2020-05-01 | 威创集团股份有限公司 | Video fusion method and device and storage medium |
| WO2021119968A1 (en) * | 2019-12-17 | 2021-06-24 | 威创集团股份有限公司 | Video fusion method and apparatus, and storage medium |
| CN111095919B (en) * | 2019-12-17 | 2021-10-08 | 威创集团股份有限公司 | Video fusion method and device and storage medium |
| WO2022133749A1 (en) * | 2020-12-22 | 2022-06-30 | Oppo广东移动通信有限公司 | Image processing method and apparatus, storage medium and electronic device |
| WO2022217525A1 (en) * | 2021-04-15 | 2022-10-20 | 深圳市大疆创新科技有限公司 | Image noise reduction processing method and device, and imaging device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106570850B (en) | 2019-06-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106570850B (en) | A kind of image interfusion method | |
| JP6803378B2 (en) | Reverse tone mapping method and equipment | |
| CN107534735B (en) | Image processing method, device and the terminal of terminal | |
| CN206042072U (en) | Two camera devices and terminal | |
| WO2017016030A1 (en) | Image processing method and terminal | |
| CN104639923B (en) | A kind of method handled view data, device and terminal | |
| CN104952036A (en) | Facial beautification method and electronic equipment in real-time video | |
| CN106570838A (en) | Image brightness optimization method and device | |
| WO2017088564A1 (en) | Image processing method, device, terminal, and storage medium | |
| JP6162345B2 (en) | Raw scene recognition that allows scene-dependent image modification before image recording or display | |
| CN110264413B (en) | Image processing method and device, electronic equipment and storage medium | |
| WO2020168465A1 (en) | Image processing device and method | |
| CN106550227B (en) | A kind of image saturation method of adjustment and device | |
| CN106506950A (en) | A kind of image processing method and device | |
| WO2024027287A9 (en) | Image processing system and method, and computer-readable medium and electronic device | |
| CN113132696A (en) | Image tone mapping method, device, electronic equipment and storage medium | |
| CN107833194A (en) | A kind of unzoned lens image recovery method of combination RAW image denoising | |
| JP6977483B2 (en) | Image processing equipment, image processing methods, image processing systems and programs | |
| CN103747222A (en) | Method and apparatus for suppressing color artifact of image | |
| CN106454101A (en) | Image processing method and terminal | |
| CN107277369A (en) | Image processing method, device, computer-readable recording medium and computer equipment | |
| CN107454318A (en) | Image processing method, device, mobile terminal and computer-readable recording medium | |
| US8150199B2 (en) | Methods and apparatus for image enhancement | |
| CN104735354A (en) | Method and device for shooting images | |
| CN105160329B (en) | A kind of tooth recognition methods, system and camera terminal based on YUV color spaces |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |