CN112070786A - Alert radar PPI image target/interference extraction method - Google Patents
Alert radar PPI image target/interference extraction method Download PDFInfo
- Publication number
- CN112070786A CN112070786A CN202010690853.8A CN202010690853A CN112070786A CN 112070786 A CN112070786 A CN 112070786A CN 202010690853 A CN202010690853 A CN 202010690853A CN 112070786 A CN112070786 A CN 112070786A
- Authority
- CN
- China
- Prior art keywords
- interference
- target
- image
- extraction
- background information
- 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
- 238000000605 extraction Methods 0.000 title claims abstract description 46
- 238000012545 processing Methods 0.000 claims abstract description 17
- 238000000034 method Methods 0.000 claims abstract description 12
- 230000000694 effects Effects 0.000 claims abstract description 5
- 238000001914 filtration Methods 0.000 claims description 5
- 230000000877 morphologic effect Effects 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 claims description 3
- 238000005286 illumination Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 3
- 238000012795 verification Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 abstract description 7
- 238000004458 analytical method Methods 0.000 abstract description 6
- 238000012544 monitoring process Methods 0.000 abstract description 3
- 238000011156 evaluation Methods 0.000 abstract description 2
- 230000007123 defense Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 241000219000 Populus Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000002592 echocardiography Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 239000003550 marker Substances 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/155—Segmentation; Edge detection involving morphological operators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- 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
- G06T2207/10032—Satellite or aerial image; Remote sensing
- G06T2207/10044—Radar 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
- G06T2207/20036—Morphological image 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
- G06T2207/30204—Marker
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Geometry (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention belongs to the technical field of alert radar interference detection and effect evaluation, and discloses an alert radar PPI image target/interference extraction method, which comprises the following steps of firstly, based on the background information coarse extraction of an interference-free PPI image: for the PPI image without interference, comparing the difference between each pixel value and the adjacent pixel value to realize the coarse extraction of background information; secondly, extracting result errors based on the background information of the non-interference PPI image: and thirdly, performing difference processing on target components in the crude extraction result of the background information to realize PPI image target/interference extraction: and taking the background extraction result of the non-interference PPI image as a reference, and performing difference processing on the PPI image containing the target/interference and the reference image to realize the extraction of the target/interference. The method and the device realize automatic detection and extraction of the target and the interference region in the warning radar PPI image, improve the processing efficiency and reduce the analysis deviation caused by human factors. The method has important significance for improving the target monitoring capability of the warning radar.
Description
Technical Field
The invention belongs to the technical field of alert radar interference detection and effect evaluation, and particularly relates to an alert radar PPI image target/interference extraction method.
Background
The warning radar is usually deployed at the frontier of frontier defense/sea defense or in the military place, and performs tasks such as searching and tracking of aerial targets and sea surface targets in a certain area around the deployment site so as to realize early warning detection of threat targets. Typically, the search results of the surveillance radar are presented on a Plan Position Indicator (PPI). On PPI, a radar antenna is positioned in the center of a display area, and radar echo processing results are displayed in a polar coordinate system and represent various echoes: the distribution of targets, interference, clutter, etc. in distance and direction will generally embed the topographic map of the radar in the result in a more general form.
When the radar is actually working, various intentional and unintentional interferences inevitably exist, and the interferences present various forms in the PPI image. In order to analyze and classify radar interference, the PPI image needs to be interpreted. Currently, interpretation work such as analysis and classification of a PPI image of a warning radar is mainly manual, so that the burden of an interpreter is very heavy, and due to the fact that various kinds of interference are in a variety, the level, accuracy and efficiency of classification of the PPI image under the condition of interference by the interpreter are not high.
In order to improve the analysis capability of the warning radar PPI image, the extraction work of the target and the interference in the PPI image needs to be carried out first, so that data support is provided for the classification of the subsequent images.
Currently, only qualitative analysis based on manual interpretation is needed for extracting targets and interferences in a warning radar PPI image, and a corresponding systematic processing technology is lacked. Reference documents:
[1] cheng, M, Mitra N J, Huang X, et al, Global consistent based solvent region detection [ J ] IEEE Transactions on Pattern Analysis and Machine Analysis, 2015,37(3): 569-: beijing Industrial Press, 2001.[3] Populus Pont, plum ancient, extract line segment [ J ] from edge image using marker growth, Shanghai university of transportation, 1999,33(4): 466-.
Disclosure of Invention
Aiming at the technical problem, the invention provides a method for extracting a target/interference of a warning radar PPI image.
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
a method for extracting a target/interference of a warning radar PPI image comprises the following steps:
firstly, coarse extraction of background information based on an undisturbed PPI image: for the PPI image without interference, comparing the difference between each pixel value and the adjacent pixel value to realize the coarse extraction of background information;
background information is mostly linear, in a local area, a pixel value of the background information jumps from a pixel value of a neighborhood of the background information, a difference between a central pixel point and a neighborhood pixel point of the local area of the image is extracted, a reasonable threshold value T1 is set, if the difference value is greater than T1, the point is determined to be an edge point, namely the background, otherwise, the point is not determined;
for each pixel (i, j) of the PPI image, constructing 8 neighborhoods of the pixel, respectively calculating the difference value between the central pixel (i, j) and the 8 neighborhoods around the central pixel (i, j), wherein the difference between the edge pixel and the peripheral neighborhood pixel is different under different conditions due to the fact that the edge background pixel value is larger than the neighborhood pixels and the PPI image is influenced by factors such as illumination and the like, and the extraction effect is good when T1-5 is selected as the threshold value of a crude extraction stage through multiple times of experimental verification;
secondly, extracting result errors based on the background information of the non-interference PPI image and eliminating the errors: removing target components in the crude extraction result of the background information, namely error components in the extraction result of the background information by using a morphological filtering method;
in the coarse extraction stage, a part of target echo region with smaller area or ground object echo region is judged as background, which belongs to error factors in background information; introducing a morphological filtering method, setting an area size threshold T2 by taking the area of a patch in a background as a measurement index, if the area of the patch is smaller than the threshold, considering that the patch belongs to a target echo or a ground object echo and does not belong to background information, removing the patch, and if the area of the patch is larger than the threshold, considering that the patch belongs to the background information and reserving the background information; the threshold T2 was set to 40 pixels in the experiment by calculating the area size of the object in the multiple images;
thirdly, PPI image target/interference extraction is realized by applying difference processing: taking a background extraction result of the non-interference PPI image as a reference, and performing difference processing on the PPI image containing the target/interference and the reference image to realize the extraction of the target/interference, wherein the specific implementation is as follows:
the gray values of the original P display image and the P display image with the target/interference are directly compared, and the pixel values of the corresponding positions are subjected to subtraction processing, so that the coordinate system, the administrative boundary and the place name label of the background clutter information are effectively eliminated, and the target/interference result is finally obtained, wherein the calculation formula is as follows:
wherein D isijIs the difference at pixel (i, j),
and
respectively representing the gray values of the pixels (i, j) in the original image and the background image, and C is a normal number in order to make the difference value not negative.
Due to the adoption of the technical scheme, the invention has the following beneficial effects:
the invention provides a PPI image target/interference extraction method, which can improve the automation degree of PPI image analysis of a warning radar, on one hand, can improve the processing efficiency, and on the other hand, can reduce the analysis deviation caused by human factors. The invention has the advantages that: firstly, roughly extracting background information based on an interference-free PPI image; secondly, extracting result errors and removing the result errors based on the background information of the non-interference PPI image; third, difference processing is applied to achieve PPI image target/interference extraction. The automatic detection and extraction of the target and the interference region in the PPI image of the warning radar are realized, so that data support is provided for classification of the target and the interference, the target extraction and image classification capability of an interpreter is effectively improved, and the method has important significance for improving the target monitoring capability of the warning radar.
Drawings
Fig. 1 is a basic flow diagram of target/disturbance extraction in PPI images.
Detailed Description
The patent is further explained below with reference to the drawings. The scope of protection of the patent is not limited to the specific embodiments.
As shown in fig. 1, the present invention proposes a target/interference extraction method for a warning radar PPI image based on an existing image processing tool, and realizes automatic detection and extraction of a target and an interference region in the warning radar PPI image, thereby providing data support for classification of the target and the interference, so as to effectively improve the target extraction and image classification capabilities of an interpreter, which is of great significance for improving the target monitoring capability of the warning radar. The specific implementation scheme is as follows:
1) in the rough extraction stage of the background information based on the interference-free PPI image, the background information is considered to be linear, and in a local area, a certain jump exists between the pixel value of the background information and the pixel value of the neighborhood thereof. Therefore, by setting a reasonable threshold T1 in consideration of the difference between the central pixel point and the neighboring pixel points in the extracted local region of the image, if the difference value is greater than T1, it is determined that the point is an edge point, i.e., the point is the background, otherwise, it is not. For each pixel (i, j) of the PPI image, constructing 8 neighborhoods of the pixel, respectively calculating the difference value between the central pixel (i, j) and the 8 neighborhoods around the central pixel (i, j), wherein the difference between the edge pixel and the peripheral neighborhood pixels is different under different conditions due to the fact that the edge (background) pixel value is larger than the neighborhood pixels and the PPI image is influenced by factors such as illumination and the like, and the extraction effect is better when T1 is selected as the threshold value of the crude extraction stage through multiple times of experimental verification.
2) And (3) eliminating errors of the background information extraction result based on the non-interference PPI image, wherein in a crude extraction stage, a part of target echo region or ground object echo region with smaller area is judged as the background, and the target echo region or the ground object echo region belongs to error factors in the background information. In order to eliminate the errors and obtain clearer background information, a morphological filtering method is introduced, the area of a patch in the background is used as a measurement index, an area size threshold T2 is set, if the area of the patch is smaller than the threshold, the patch is considered to belong to a target echo or a ground object echo and not belong to background information, the patch is eliminated, and if the area of the patch is larger than the threshold, the patch is considered to be background information and is reserved. The threshold T2 was set to 40 pixels in the experiment by calculating the area size of the object in the multiple images.
3) PPI image target/interference extraction using difference processing
Taking the background clutter information extracted by the previous two steps of processing as a reference, directly comparing gray values of an original P display image and the P display image with a target/interference, and performing subtraction processing on pixel values at corresponding positions, thereby effectively eliminating background clutter information (a coordinate system, an administrative boundary, a place name label and the like), and finally obtaining a target/interference result, wherein a calculation formula is as follows:
wherein D isijIs the difference at pixel (i, j),
and
respectively representing the gray values of the pixels (i, j) in the original image and the background image, and C is a normal number in order to make the difference value not negative.
Claims (1)
1. A method for extracting a target/interference of a warning radar PPI image is characterized by comprising the following steps: the method comprises the following steps:
firstly, coarse extraction of background information based on an undisturbed PPI image: for the PPI image without interference, comparing the difference between each pixel value and the adjacent pixel value to realize the coarse extraction of background information;
the adopted background information is mostly linear, in a local area, the pixel value of the background information jumps from the pixel value of the neighborhood thereof, the difference between the central pixel point and the neighborhood pixel point of the local area of the image is extracted, and a reasonable threshold value T1 is set, if the difference value is greater than the threshold value T1, the point is determined to be an edge point, namely the background, otherwise, the point is not determined;
for each pixel (i, j) of the PPI image, constructing 8 neighborhoods of the pixel, respectively calculating the difference value between the central pixel (i, j) and the 8 neighborhoods around the central pixel (i, j), wherein the difference between the edge background pixel value and the neighborhood pixel is different under different conditions due to the fact that the edge background pixel value is larger than the neighborhood pixel value and the PPI image is influenced by illumination factors, and the extraction effect is good when the threshold value T1 is selected to be 5 as the threshold value of the coarse extraction stage through multiple times of experimental verification;
secondly, extracting result errors based on the background information of the non-interference PPI image and eliminating the errors: removing target components in the crude extraction result of the background information, namely error components in the extraction result of the background information by using a morphological filtering method;
in the coarse extraction stage, a part of target echo region with smaller area or ground object echo region is judged as background, which belongs to error factors in background information; introducing a morphological filtering method, setting an area size threshold T2 by taking the area of a patch in a background as a measurement index, if the area of the patch is smaller than the threshold, considering that the patch belongs to a target echo or a ground object echo and does not belong to background information, removing the patch, and if the area of the patch is larger than the threshold, considering that the patch belongs to the background information and reserving the background information; the threshold T2 was set to 40 pixels in the experiment by calculating the area size of the object in the multiple images;
thirdly, PPI image target/interference extraction is realized by applying difference processing: taking a background extraction result of the non-interference PPI image as a reference, and performing difference processing on the PPI image containing the target/interference and the reference image to realize the extraction of the target/interference, wherein the specific implementation is as follows:
the gray values of the original P display image and the P display image with the target/interference are directly compared, and the pixel values of the corresponding positions are subjected to subtraction processing, so that the coordinate system, the administrative boundary and the place name label of the background clutter information are effectively eliminated, and the target/interference result is finally obtained, wherein the calculation formula is as follows:
wherein D isijIs the difference at pixel (i, j),
and
respectively representing the gray values of the pixels (i, j) in the original image and the background image, and C is a normal number in order to make the difference value not negative.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010690853.8A CN112070786B (en) | 2020-07-17 | 2020-07-17 | Method for extracting warning radar PPI image target and interference |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010690853.8A CN112070786B (en) | 2020-07-17 | 2020-07-17 | Method for extracting warning radar PPI image target and interference |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112070786A true CN112070786A (en) | 2020-12-11 |
| CN112070786B CN112070786B (en) | 2023-11-24 |
Family
ID=73657073
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010690853.8A Active CN112070786B (en) | 2020-07-17 | 2020-07-17 | Method for extracting warning radar PPI image target and interference |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112070786B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113096026A (en) * | 2021-02-26 | 2021-07-09 | 梅卡曼德（北京）机器人科技有限公司 | Image processing method, image processing apparatus, electronic device, and medium |
| CN114814840A (en) * | 2022-03-28 | 2022-07-29 | 河南大学 | Method and system for image screening and interference position detection of interference-containing synthetic aperture radar |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009031939A (en) * | 2007-07-25 | 2009-02-12 | Advanced Telecommunication Research Institute International | Image processing apparatus, method and program |
| CN103413278A (en) * | 2013-08-22 | 2013-11-27 | 成都数之联科技有限公司 | Method for filtering commodity picture background noise |
| CN104199009A (en) * | 2014-09-18 | 2014-12-10 | 中国民航科学技术研究院 | Radar image clutter suppression method based on time-domain characteristics |
| CN104899866A (en) * | 2015-05-05 | 2015-09-09 | 河南三联网络技术有限公司 | Intelligent infrared small target detection method |
| CN107204006A (en) * | 2017-06-01 | 2017-09-26 | 大连海事大学 | A kind of static target detection method based on double background difference |
| CN107886498A (en) * | 2017-10-13 | 2018-04-06 | 中国科学院上海技术物理研究所 | A kind of extraterrestrial target detecting and tracking method based on spaceborne image sequence |
| CN108280841A (en) * | 2018-01-16 | 2018-07-13 | 北京联合大学 | A kind of foreground extracting method based on neighborhood territory pixel intensity correction |
| CN109711256A (en) * | 2018-11-27 | 2019-05-03 | 天津津航技术物理研究所 | A kind of low latitude complex background unmanned plane target detection method |
-
2020
- 2020-07-17 CN CN202010690853.8A patent/CN112070786B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009031939A (en) * | 2007-07-25 | 2009-02-12 | Advanced Telecommunication Research Institute International | Image processing apparatus, method and program |
| CN103413278A (en) * | 2013-08-22 | 2013-11-27 | 成都数之联科技有限公司 | Method for filtering commodity picture background noise |
| CN104199009A (en) * | 2014-09-18 | 2014-12-10 | 中国民航科学技术研究院 | Radar image clutter suppression method based on time-domain characteristics |
| CN104899866A (en) * | 2015-05-05 | 2015-09-09 | 河南三联网络技术有限公司 | Intelligent infrared small target detection method |
| CN107204006A (en) * | 2017-06-01 | 2017-09-26 | 大连海事大学 | A kind of static target detection method based on double background difference |
| CN107886498A (en) * | 2017-10-13 | 2018-04-06 | 中国科学院上海技术物理研究所 | A kind of extraterrestrial target detecting and tracking method based on spaceborne image sequence |
| CN108280841A (en) * | 2018-01-16 | 2018-07-13 | 北京联合大学 | A kind of foreground extracting method based on neighborhood territory pixel intensity correction |
| CN109711256A (en) * | 2018-11-27 | 2019-05-03 | 天津津航技术物理研究所 | A kind of low latitude complex background unmanned plane target detection method |
Non-Patent Citations (5)
| Title |
|---|
| MA BAI-XUE ET.AL: "Marine SAR image segmentation and edge gradient feature extraction", 《 COMPUTER ENGINEERING AND DESIGN》, vol. 34, no. 8, pages 2796 - 800 * |
| 李廷鹏 等: "基于GRNN和PNN的复杂电磁环境效应机理分析", 《现代电子技术》, vol. 41, no. 23, pages 145 - 152 * |
| 王铎: "基于形态学和邻域差值的红外小目标检测算法", 《光电技术应用》 * |
| 王铎: "基于形态学和邻域差值的红外小目标检测算法", 《光电技术应用》, no. 02, 15 April 2016 (2016-04-15), pages 23 - 25 * |
| 黎航: "天空背景下弱小目标检测与跟踪方法研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》, pages 032 - 25 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113096026A (en) * | 2021-02-26 | 2021-07-09 | 梅卡曼德（北京）机器人科技有限公司 | Image processing method, image processing apparatus, electronic device, and medium |
| CN114814840A (en) * | 2022-03-28 | 2022-07-29 | 河南大学 | Method and system for image screening and interference position detection of interference-containing synthetic aperture radar |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112070786B (en) | 2023-11-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108510467B (en) | SAR image target identification method based on depth deformable convolution neural network | |
| CN102609701B (en) | Remote sensing detection method based on optimal scale for high-resolution SAR (synthetic aperture radar) | |
| CN106022288B (en) | The identification of marine oil spill information and extracting method based on SAR image | |
| Musman et al. | Automatic recognition of ISAR ship images | |
| CN108229342B (en) | Automatic sea surface ship target detection method | |
| CN110031843B (en) | ROI (region of interest) -based SAR (synthetic Aperture Radar) image target positioning method, system and device | |
| CN103020605B (en) | Bridge identification method based on decision-making layer fusion | |
| CN110443201B (en) | Target identification method based on multi-source image joint shape analysis and multi-attribute fusion | |
| CN109471098B (en) | Airport runway foreign matter detection method utilizing FOD radar phase coherence information | |
| CN111079596A (en) | System and method for identifying typical marine artificial target of high-resolution remote sensing image | |
| CN103020592B (en) | A kind of remote sensing images naval vessel based on local context detects false-alarm elimination method | |
| CN109635733B (en) | Parking lot and vehicle target detection method based on visual saliency and queue correction | |
| CN102254191B (en) | Rainfall particle phase identification method based on image processing | |
| CN105719283A (en) | Road surface crack image detection method based on Hessian matrix multi-scale filtering | |
| CN107862271B (en) | Detection method of ship target | |
| CN107239755A (en) | Offshore oil and gas platform extraction system based on high score satellite remote sensing date | |
| CN110070545B (en) | Method for automatically extracting urban built-up area by urban texture feature density | |
| CN112070786A (en) | Alert radar PPI image target/interference extraction method | |
| CN111353371A (en) | Coastline extraction method based on satellite-borne SAR image | |
| Rabee et al. | License plate detection and recognition in complex scenes using mathematical morphology and support vector machines | |
| CN116109936B (en) | Target detection and identification method based on optical remote sensing | |
| Xie et al. | Fast ship detection from optical satellite images based on ship distribution probability analysis | |
| Kushwaha et al. | Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images. | |
| CN105205801A (en) | Method and device for extracting sea reclamation information based on change detection | |
| CN111428624B (en) | Optical remote sensing image on-orbit ship target detection 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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |