CN108428218A - A kind of image processing method of removal newton halation - Google Patents
A kind of image processing method of removal newton halation Download PDFInfo
- Publication number
- CN108428218A CN108428218A CN201810167030.XA CN201810167030A CN108428218A CN 108428218 A CN108428218 A CN 108428218A CN 201810167030 A CN201810167030 A CN 201810167030A CN 108428218 A CN108428218 A CN 108428218A
- Authority
- CN
- China
- Prior art keywords
- image
- halation
- processing method
- newton
- denoising
- 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
- 238000003672 processing method Methods 0.000 title claims abstract description 15
- 238000001514 detection method Methods 0.000 claims abstract description 16
- 238000006243 chemical reaction Methods 0.000 claims abstract description 10
- 238000012216 screening Methods 0.000 claims abstract description 10
- 238000012545 processing Methods 0.000 claims abstract description 9
- 238000000034 method Methods 0.000 claims abstract description 8
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 5
- 238000000605 extraction Methods 0.000 claims abstract description 5
- 238000004458 analytical method Methods 0.000 claims abstract description 4
- 230000005764 inhibitory process Effects 0.000 abstract description 5
- 230000019771 cognition Effects 0.000 abstract description 2
- 238000010801 machine learning Methods 0.000 abstract description 2
- 238000012544 monitoring process Methods 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
Classifications
-
- G06T5/70—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
Abstract
The present invention provides a kind of image processing method of removal newton halation, and pending picture is carried out double format conversions；Picture size after progress double format conversions is pre-processed, obtain image data, utilize background modeling extraction image pattern effective coverage, analysis and machine learning are carried out to halation sample, HSV decomposition is carried out to noise image, take out luminance component, the present invention does not limit denoising method, background modeling is to establish rationally true background for image, image pattern screening is to utilize color of image and size primary screener and artificial fining screening, image-region cognition is using color of image statistical information and image moment information as the characteristic of division of image, image restrainable algorithms are recycled to carry out inhibition processing to the halation in the region.The present invention after obtaining video to video in the halation target that occurs be identified and detect, and halation inhibition is carried out to detection zone, improves the readability of video monitoring picture.
Description
Technical field
The present invention is a kind of image processing method of removal newton halation, belongs to technical field of image processing.
Background technology
In the prior art, image is that the mankind obtain the most important mode of information, and the mankind obtain the 80% of information according to statistics
Derived from image.Image is mapping of the three dimensional physical world in two dimensional surface.In general, the image of video camera shooting can pass through ISP
(Imagesignal processing) process flow, generally comprises following steps：Sensor photosensitive → color interpolation
→ image denoising → white balance → color correction → Gamma correction → edge enhancing → image output.In this process, image
Denoising is for removing noise in image, including interpolation noise, dark noise and truncation noise etc..In the same of removal noise
When, also the part details of image, especially sharp keen edge details are eliminated together, and there are newton for traditional picture
The problem of halation, it is inconvenient that the prior art there is a problem of taking out, so needing a kind of new technology to solve the above problems.
Invention content
In view of the deficienciess of the prior art, it is an object of the present invention to provide a kind of picture processing sides of removal newton halation
Method, to solve the problems mentioned in the above background technology, easy to use, easy to operation, high treating effect of the invention, reliability
It is high.
To achieve the goals above, the present invention is to realize by the following technical solutions：A kind of removal newton halation
Image processing method includes the following steps：
S1：Pending picture is carried out double format conversions by Image Acquisition；Picture after progress double format conversions is big
It is small to be pre-processed, obtain image data；
S2：Image pattern learns, and using background modeling extraction image pattern effective coverage, analysis and machine are carried out to halation sample
Study carries out HSV decomposition to noise image, takes out luminance component：If I (x, y) be containing noise pollution, without denoising at
The real image of reason, S (x, y) they are to carry out the result images after denoising to I (x, y), and the two is RGB color format, and
Size is M × N, and the present invention does not limit denoising method, any image denoising processing method effectively can to use
To carry out denoising to I (x, y) to obtain S (x, y)；I (x, y) and S (x, y) are transformed into hsv color space respectively, respectively
The two images Ihsv (x, y) and Shsv (x, y) in hsv color space are obtained, the luminance component of the two is taken out, calculates image slices
Plain approximating variances；
S3：Image-region recognizes, and carries out target location region detection to processing image, is put down to each element of image array
Side calculates, and element value of the obtained new value as corresponding position obtains the new image array of a width.
Further, the background modeling is to establish rationally true background for image.
Further, the target location region detection is using half-tone information and image connectivity region to target location
Domain carries out primary detection, and grader is recycled to further confirm that primary detection zone.
Further, described image screening sample is to utilize color of image and size primary screener and artificial fining
Screening.
Beneficial effects of the present invention：The present invention a kind of removal newton halation image processing method, background modeling be for
Image establishes rationally true background, and image pattern screening is using color of image and size primary screener and manually fine
Change screening, image-region cognition is used for using color of image statistical information and image moment information as the characteristic of division of image
The construction of grader, halation inhibition are to confirm that image target area contains halation phenomenon using grader, and image is recycled to inhibit
Algorithm carries out inhibition processing to the halation in the region.The present invention after obtaining video to video in the halation target that occurs know
Not with detection, and to detection zone carry out halation inhibition, improve the readability of video monitoring picture.
Specific implementation mode
To make the technical means, the creative features, the aims and the efficiencies achieved by the present invention be easy to understand, with reference to
Specific implementation mode, the present invention is further explained.
The present invention provides a kind of technical solution：A kind of image processing method of removal newton halation, includes the following steps：
S1：Pending picture is carried out double format conversions by Image Acquisition；Picture after progress double format conversions is big
It is small to be pre-processed, obtain image data；
S2：Image pattern learns, and using background modeling extraction image pattern effective coverage, analysis and machine are carried out to halation sample
Study carries out HSV decomposition to noise image, takes out luminance component：If I (x, y) be containing noise pollution, without denoising at
The real image of reason, S (x, y) they are to carry out the result images after denoising to I (x, y), and the two is RGB color format, and
Size is M × N, and the present invention does not limit denoising method, any image denoising processing method effectively can to use
To carry out denoising to I (x, y) to obtain S (x, y)；I (x, y) and S (x, y) are transformed into hsv color space respectively, respectively
The two images Ihsv (x, y) and Shsv (x, y) in hsv color space are obtained, the luminance component of the two is taken out, calculates image slices
Plain approximating variances；
S3：Image-region recognizes, and carries out target location region detection to processing image, is put down to each element of image array
Side calculates, and element value of the obtained new value as corresponding position obtains the new image array of a width.
The background modeling is to establish rationally true background for image, and the target location region detection is to utilize gray scale
Information and image connectivity region carry out primary detection to target region, and grader is recycled to carry out primary detection zone
It further confirms that, described image screening sample is to utilize color of image and size primary screener and artificial fining screening.
Embodiment 1：Pending picture is subjected to double format conversions；Picture after progress double format conversions is big
It is small to be pre-processed, image data is obtained, using background modeling extraction image pattern effective coverage, halation sample is analyzed
With machine learning, HSV decomposition is carried out to noise image, takes out luminance component：If I (x, y) be containing noise pollution, without
The real image of denoising, S (x, y) are to carry out the result images after denoising to I (x, y), and the two is RGB color lattice
Formula, and size is M × N, the present invention does not limit denoising method, any effectively image denoising processing method all may be used
To be used for carrying out denoising to I (x, y) to obtain S (x, y)；I (x, y) and S (x, y) are transformed into hsv color space respectively,
The two images Ihsv (x, y) and Shsv (x, y) in hsv color space are respectively obtained, the luminance component of the two is taken out, calculates figure
As pixel approximating variances, target location region detection is carried out to processing image, a square meter is carried out to each element of image array
It calculates, element value of the obtained new value as corresponding position obtains the new image array of a width.
The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention, for this field skill
For art personnel, it is clear that invention is not limited to the details of the above exemplary embodiments, and without departing substantially from the present invention spirit or
In the case of essential characteristic, the present invention can be realized in other specific forms.Therefore, in all respects, should all incite somebody to action
Embodiment regards exemplary as, and is non-limiting, the scope of the present invention by appended claims rather than on state
Bright restriction, it is intended that including all changes that come within the meaning and range of equivalency of the claims in the present invention
It is interior.Claim should not be considered as and be limited the claims involved.
In addition, it should be understood that although this specification is described in terms of embodiments, but not each embodiment is only wrapped
Containing an independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art should
It considers the specification as a whole, the technical solutions in the various embodiments may also be suitably combined, forms those skilled in the art
The other embodiment being appreciated that.
Claims (4)
1. a kind of image processing method of removal newton halation, it is characterised in that include the following steps：
S1：Pending picture is carried out double format conversions by Image Acquisition；Picture after progress double format conversions is big
It is small to be pre-processed, obtain image data；
S2：Image pattern learns, and using background modeling extraction image pattern effective coverage, analysis and machine are carried out to halation sample
Study carries out HSV decomposition to noise image, takes out luminance component：If I (x, y) be containing noise pollution, without denoising at
The real image of reason, S (x, y) they are to carry out the result images after denoising to I (x, y), and the two is RGB color format, and
Size is M × N, and the present invention does not limit denoising method, any image denoising processing method effectively can to use
To carry out denoising to I (x, y) to obtain S (x, y)；I (x, y) and S (x, y) are transformed into hsv color space respectively, respectively
The two images Ihsv (x, y) and Shsv (x, y) in hsv color space are obtained, the luminance component of the two is taken out, calculates image slices
Plain approximating variances；
S3：Image-region recognizes, and carries out target location region detection to processing image, is put down to each element of image array
Side calculates, and element value of the obtained new value as corresponding position obtains the new image array of a width.
2. a kind of image processing method of removal newton halation according to claim 1, it is characterised in that：The background is built
Mould is to establish rationally true background for image.
3. a kind of image processing method of removal newton halation according to claim 1, it is characterised in that：The target position
It is to carry out primary detection to target region using half-tone information and image connectivity region to set region detection, recycles grader
Primary detection zone is further confirmed that.
4. a kind of image processing method of removal newton halation according to claim 1, it is characterised in that：Described image sample
This screening is to utilize color of image and size primary screener and artificial fining screening.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810167030.XA CN108428218A (en) | 2018-02-28 | 2018-02-28 | A kind of image processing method of removal newton halation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810167030.XA CN108428218A (en) | 2018-02-28 | 2018-02-28 | A kind of image processing method of removal newton halation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108428218A true CN108428218A (en) | 2018-08-21 |
Family
ID=63157217
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810167030.XA Pending CN108428218A (en) | 2018-02-28 | 2018-02-28 | A kind of image processing method of removal newton halation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108428218A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110455747A (en) * | 2019-07-19 | 2019-11-15 | 浙江师范大学 | It is a kind of based on deep learning without halo effect white light phase imaging method and system |
| CN110991458A (en) * | 2019-11-25 | 2020-04-10 | 创新奇智(北京)科技有限公司 | Artificial intelligence recognition result sampling system and sampling method based on image characteristics |
| CN111260573A (en) * | 2020-01-13 | 2020-06-09 | 浙江未来技术研究院(嘉兴) | Method for eliminating vignetting phenomenon in surgical microscopic imaging |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090074317A1 (en) * | 2007-09-19 | 2009-03-19 | Samsung Electronics Co., Ltd. | System and method for reducing halo effect in image enhancement |
| CN103714352A (en) * | 2013-12-26 | 2014-04-09 | 黄廷磊 | Halation inhibition method based on image cognition region |
| CN104318524A (en) * | 2014-10-15 | 2015-01-28 | 烟台艾睿光电科技有限公司 | Method, device and system for image enhancement based on YCbCr color space |
| CN105243651A (en) * | 2015-11-19 | 2016-01-13 | 中国人民解放军国防科学技术大学 | Image edge enhancement method based on approximate variance and dark block pixel statistic information |
| CN107016657A (en) * | 2017-04-07 | 2017-08-04 | 河北工业大学 | The restorative procedure of the face picture covered by reticulate pattern |
-
2018
- 2018-02-28 CN CN201810167030.XA patent/CN108428218A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090074317A1 (en) * | 2007-09-19 | 2009-03-19 | Samsung Electronics Co., Ltd. | System and method for reducing halo effect in image enhancement |
| CN103714352A (en) * | 2013-12-26 | 2014-04-09 | 黄廷磊 | Halation inhibition method based on image cognition region |
| CN104318524A (en) * | 2014-10-15 | 2015-01-28 | 烟台艾睿光电科技有限公司 | Method, device and system for image enhancement based on YCbCr color space |
| CN105243651A (en) * | 2015-11-19 | 2016-01-13 | 中国人民解放军国防科学技术大学 | Image edge enhancement method based on approximate variance and dark block pixel statistic information |
| CN107016657A (en) * | 2017-04-07 | 2017-08-04 | 河北工业大学 | The restorative procedure of the face picture covered by reticulate pattern |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110455747A (en) * | 2019-07-19 | 2019-11-15 | 浙江师范大学 | It is a kind of based on deep learning without halo effect white light phase imaging method and system |
| CN110455747B (en) * | 2019-07-19 | 2021-09-28 | 浙江师范大学 | Deep learning-based white light phase imaging method and system without halo effect |
| CN110991458A (en) * | 2019-11-25 | 2020-04-10 | 创新奇智(北京)科技有限公司 | Artificial intelligence recognition result sampling system and sampling method based on image characteristics |
| CN110991458B (en) * | 2019-11-25 | 2023-05-23 | 创新奇智(北京)科技有限公司 | Image feature-based artificial intelligent recognition result sampling system and sampling method |
| CN111260573A (en) * | 2020-01-13 | 2020-06-09 | 浙江未来技术研究院(嘉兴) | Method for eliminating vignetting phenomenon in surgical microscopic imaging |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105608671B (en) | A kind of image split-joint method based on SURF algorithm | |
| CN104749184B (en) | Automatic optical detection method and system | |
| CN105279372B (en) | A kind of method and apparatus of determining depth of building | |
| US8005264B2 (en) | Method of automatically detecting and tracking successive frames in a region of interesting by an electronic imaging device | |
| CN105844630B (en) | A kind of image super-resolution fusion denoising method of binocular vision | |
| WO2013135033A1 (en) | Tunnel deformation online monitoring system based on image analysis and application thereof | |
| CN107507173A (en) | A kind of full slice image without refer to intelligibility evaluation method and system | |
| CN107358627B (en) | Fruit size detection method based on Kinect camera | |
| CN103426182A (en) | Electronic image stabilization method based on visual attention mechanism | |
| CN111915704A (en) | Apple hierarchical identification method based on deep learning | |
| CN108428218A (en) | A kind of image processing method of removal newton halation | |
| CN111739031B (en) | Crop canopy segmentation method based on depth information | |
| CN105787943B (en) | SAR image registration method based on multi-scale image block feature and rarefaction representation | |
| CN109166125A (en) | A kind of three dimensional depth image partitioning algorithm based on multiple edge syncretizing mechanism | |
| WO2008111550A1 (en) | Image analysis system and image analysis program | |
| CN108377374A (en) | Method and system for generating depth information related to an image | |
| CN108229524A (en) | A kind of chimney and condensing tower detection method based on remote sensing images | |
| Panetta et al. | Logarithmic Edge Detection with Applications. | |
| CN106228541A (en) | The method and device of screen location in vision-based detection | |
| Mai et al. | Back propagation neural network dehazing | |
| CN114022383A (en) | Moire pattern removing method and device for character image and electronic equipment | |
| CN110223356A (en) | A kind of monocular camera full automatic calibration method based on energy growth | |
| CN110532935A (en) | A kind of high-throughput reciprocity monitoring system of field crop phenotypic information and monitoring method | |
| CN106570879A (en) | Image processing method applied in large screen interactive system | |
| CN108830834B (en) | Automatic extraction method for video defect information of cable climbing robot |
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: 20180821 |