CN111862227A - On-orbit non-uniformity correction method of mechanical staggered splicing type camera based on complex scene - Google Patents
On-orbit non-uniformity correction method of mechanical staggered splicing type camera based on complex scene Download PDFInfo
- Publication number
- CN111862227A CN111862227A CN202010350911.2A CN202010350911A CN111862227A CN 111862227 A CN111862227 A CN 111862227A CN 202010350911 A CN202010350911 A CN 202010350911A CN 111862227 A CN111862227 A CN 111862227A
- Authority
- CN
- China
- Prior art keywords
- image
- data
- yaw
- coefficient
- correction
- 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
- 238000012937 correction Methods 0.000 title claims abstract description 54
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000003384 imaging method Methods 0.000 claims abstract description 46
- 238000012545 processing Methods 0.000 claims abstract description 7
- 239000000523 sample Substances 0.000 claims description 17
- 238000001514 detection method Methods 0.000 claims description 10
- 238000003491 array Methods 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 8
- 238000013519 translation Methods 0.000 claims description 5
- 239000011159 matrix material Substances 0.000 claims description 4
- 238000013139 quantization Methods 0.000 claims description 2
- 238000013461 design Methods 0.000 claims 1
- 238000002474 experimental method Methods 0.000 abstract 1
- 238000001444 catalytic combustion detection Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012887 quadratic function Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000002123 temporal 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
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Transforming Light Signals Into Electric Signals (AREA)
Abstract
The invention relates to an on-orbit relative calibration method of a mechanical staggered splicing type remote sensing camera based on a complex scene. The technology comprises the steps of carrying out orthogonal secondary imaging on a complex scene before and after the camera rotates and carrying out non-uniformity correction through gray value multi-point curve fitting by utilizing the characteristic that a satellite can rotate around a yaw axis of the satellite, so as to achieve the purpose of carrying out non-uniformity correction on the mechanical staggered splicing type CCD camera. Experiments show that the technology can effectively reduce the nonuniformity of the CCD camera, improve the quality of remote sensing images and provide effective data for subsequent image processing.
Description
Technical Field
The invention relates to an image processing technology, in particular to an on-orbit relative calibration method for a mechanical staggered splicing type remote sensing camera based on a complex scene.
Background
With the development of the space remote sensing technology, high spatial and temporal resolution and wide field of view gradually become the research focus of the push-broom type space remote sensing camera. In order to enable the push-broom space camera to have a wider field of view, the size of a single CCD device cannot meet the current requirements, multiple CCD devices need to be spliced in a staggered mode to achieve large-field-of-view imaging, and an in-orbit satellite has a larger imaging width.
For the push-broom imaging optical remote sensing satellite with strong agility, when in-orbit relative radiation calibration is carried out, a method of rotating a camera by a certain angle (generally about 90 degrees) around a satellite yaw axis can be used for acquiring a relatively uniform image so as to carry out non-uniformity correction among different probe elements. This is called the Side-slither scaling method, also known as yaw scaling.
The mechanical staggered splicing type CCD camera focal plane is formed by assembling a plurality of CCDs into a two-line staggered focal plane, namely, the CCDs in the second line just fill in gaps formed by the CCDs in the first line, the pixels at the head and the tail are respectively aligned, but the two lines are staggered for a certain position in the flying direction (image integration direction) of the camera. When the non-uniformity correction is carried out by using the traditional yaw calibration method, the non-uniformity between two rows of CCDs is difficult to reduce, and the phenomenon of stripe non-uniformity exists in the corrected image.
Disclosure of Invention
In order to solve the problem of stripe nonuniformity existing when the traditional yaw calibration method is used for carrying out nonuniformity correction on a mechanical staggered and spliced CCD camera, the invention provides an on-orbit relative calibration method for the mechanical staggered and spliced remote sensing camera based on a complex scene.
The invention provides an on-orbit relative calibration method of a mechanical staggered splicing type remote sensing camera based on a complex scene, which is based on a yaw calibration method and the mechanical staggered splicing characteristic of a CCD (charge coupled device) camera, and reduces the nonuniformity of images through two corrections before and after the camera rotates; the specific process comprises the following steps:
step 1: and inputting the image data of the yaw imaging mode to obtain a gray matrix of the yaw imaging data. Due to the characteristic of the staggered splicing focal planes, imaging among the yaw imaging slices is discontinuous, so that an area imaged by one sensor needs to be intercepted, the degree of a connecting line included angle in an actual yaw radiometric calibration image is calculated by using an LSD (line Segment detector) linear detection algorithm, and the yaw radiometric calibration data is subjected to specified processing according to the detection result of the included angle of the yaw radiometric calibration data, so that each line of data in the image is ensured to be imaging data of all probe elements of the sensor on the same ground object;
Step 2: using the data in the step 1, carrying out multi-point curve fitting on the imaging elements of the probe elements by a least square method, solving the non-uniformity correction coefficient of each probe element in each array of the focal plane, and correcting the conventional imaging mode image by using the coefficient;
and step 3: and (3) carrying out multipoint curve fitting on the adjacent array splicing pixels by using the corrected image obtained in the step (2) through a least square method, solving a non-uniformity correction coefficient between focal plane arrays, and correcting the image by using the coefficient.
Further, the step 2 specifically comprises:
firstly, according to the method of the step 1, the yaw radiometric calibration data is subjected to specified processing, so that pixels in each row are images of the same ground object; then, solving the gray level average value of each row of pixels to obtain average value data of a row of pixels; then, taking each line of data, and calculating a conversion coefficient between the line of data and pixel average value data by using a least square method, wherein the coefficient is a non-uniformity correction coefficient; and finally, correcting the image in the conventional imaging mode by using the correction coefficient.
Further, the step 3 specifically includes:
firstly, taking an overlapped part image group from a conventional imaging mode image after first correction; then, after the group data of each image is aligned in a translation mode, taking N lines of data groups in the middle of each image group (N can be set according to the pixel width of an overlapping area); then, a least square method is used for solving a conversion coefficient among all data groups, wherein the coefficient is a non-uniformity correction coefficient among the CCD arrays; and finally, performing second correction on the image in the conventional imaging mode by using the correction coefficient.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
the method is suitable for the non-uniformity correction of the mechanical staggered splicing type CCD camera, solves the problem of stripe non-uniformity existing when the traditional yaw scaling method is used for carrying out the non-uniformity correction on the mechanical staggered splicing type CCD camera, effectively reduces the image non-uniformity, and has good applicability.
Drawings
FIG. 1 is a general flow diagram of the present invention;
FIG. 2 is a schematic view of a mechanically staggered CCD camera focal plane
FIG. 3 is an uncorrected conventional imaging mode image;
FIG. 4 is a yaw imaging mode image;
FIG. 5 is a degree of link angle in a yaw radiometric calibration image;
FIG. 6 is a yaw radiometric calibration image normalization;
FIG. 7 is an image after a first correction;
fig. 8 is an image contrast map before and after correction.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the attached drawings:
the invention relates to an on-orbit relative calibration method of a mechanical staggered splicing type remote sensing camera based on a complex scene, wherein a non-uniformity correction algorithm is based on a yaw calibration method and the mechanical staggered splicing characteristic of a TDICCD camera, and the non-uniformity of an image is reduced through twice corrections before and after the camera rotates, and the flow is shown in figure 1.
The non-uniformity correction method for the mechanical staggered splicing type TDICCD camera comprises the following specific processes:
step 1: and inputting the image data of the yaw imaging mode to obtain a gray matrix of the yaw imaging data. Due to the characteristic of the staggered splicing focal planes, imaging among the yaw imaging slices is discontinuous, so that an area imaged by one sensor needs to be intercepted, the degree of a connecting line included angle in an actual yaw radiometric calibration image is calculated by using an LSD (line Segment detector) linear detection algorithm, and the yaw radiometric calibration data is subjected to specified processing according to the detection result of the included angle of the yaw radiometric calibration data, so that each line of data in the image is ensured to be imaging data of all probe elements of the sensor on the same ground object;
step 2: firstly, the available yaw imaging mode image data determined in the step 1 are translated and divided into two image blocks according to odd and even serial numbers as shown in fig. 2, so that the pixels in each row of each image block are images of the same ground object; then, solving the gray level average value of each row of pixels to obtain the average value data of two columns of pixels; taking each line of data, carrying out multi-point curve fitting on the line of data and the average value data of the corresponding pixels, and calculating a conversion coefficient between the line of data and the average value data of the corresponding pixels by using a least square method, wherein the coefficient is a non-uniformity correction coefficient; and finally, correcting the image in the conventional imaging mode by using the correction coefficient.
And step 3: firstly, splicing a part of image groups (image data formed by an overlapping area in FIG. 2) in a conventional imaging mode image after first correction; then, after the group data of each image is aligned in a translation mode, taking N rows of data groups (N can be set according to the pixel width of an overlapping area) in the middle of each image group; then, carrying out multi-point curve fitting on each data group by using a least square method, and solving a conversion coefficient between each data group, wherein the coefficient is a non-uniformity correction coefficient between TDICCD arrays; and finally, performing second correction on the image in the conventional imaging mode by using the correction coefficient.
Specific non-uniformity correction examples are shown below:
FIG. 3 is an uncorrected conventional imaging mode image, and clearly shows both a narrow band non-uniformity (inter-pixel non-uniformity) and a wider band non-uniformity (inter-array non-uniformity). Fig. 4 is an image of the yaw imaging mode, and it is obvious that the 1 st, 3 rd and 5 th blocks are consistent, and the 2 nd and 4 th blocks are consistent, because there is a certain interval between two rows of CCD arrays, and the objects are different in the imaging of the yaw mode.
The application step one: and inputting the image data of the yaw imaging mode to obtain a gray matrix of the yaw imaging data. Due to the characteristic of the staggered splicing focal planes, imaging among the yaw imaging slices is discontinuous, so that an area imaged by one sensor needs to be intercepted, the degree of a connecting line included angle in an actual yaw radiometric calibration image is calculated by using an LSD (line Segment detector) linear detection algorithm, and the yaw radiometric calibration data is subjected to specified processing according to the detection result of the included angle of the yaw radiometric calibration data, so that each line of data in the image is ensured to be imaging data of all probe elements of the sensor on the same ground object. The results of the line angle detection are shown in FIG. 5, and the yaw calibration data are defined in FIG. 6.
The prescribed formula is as follows:
in the formula, the following components are mixed; DN (i, j) represents the gray value of the image at j column of ith row specified by the yaw data; DNSSDefining an image gray value before quantization for the yaw radiometric calibration image; and theta is the actual included angle of the yaw image.
And the application step two: using the data specified in the step 1, solving the conversion relation between the row pixel gray value formed by each probe element and the row pixel gray average value by a least square method, namely solving the non-uniformity correction coefficient of each probe element in each array of the focal plane, and correcting the conventional imaging mode image by using the coefficient so as to achieve the non-uniformity correction among all probe elements in the single-chip probe array, wherein the correction result is shown in fig. 7;
solving the correction coefficient by using a least square method to make a row of pixel gray values formed by a certain probe element to be corrected be { x }i1,2, r, the gray level mean value of each row of pixels formed by each probe element is listed as { y {i|i＝1,2,...,r}，xi,yiComposing a set of discrete points in a plane (x)i,yi) And (i) 1,2, a., r, performing multi-point curve fitting on the discrete point set by using the following formula, wherein each coefficient of the fitting curve is a correction coefficient.
Linear fitting in linear form y ═ a0+a1x, the formula for solving the coefficients is:
fitting curve y ═ a of quadratic function 0+a1x+a2x2The formula for solving the coefficients is:
in the formula, r is the number of discrete points; { a0,a1,...,anThe coefficients of the fitted curve terms are.
The application step three: and (3) solving the conversion coefficient of each adjacent array by using the corrected image obtained in the step (2) and the least square method in the step (2) among splicing areas due to the fact that the corrected image is a mechanical staggered splicing type camera, namely solving the non-uniformity correction coefficient among focal plane arrays, and correcting the image by using the coefficient so as to achieve the purpose that the correction result among the detection arrays is shown in figure 8, and the image non-uniformity is reduced to 0.660% from 6.236%.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only illustrative of the present invention and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. An on-orbit relative calibration method of a mechanical staggered splicing type remote sensing camera based on a complex scene is characterized in that the method is based on the mechanical staggered splicing characteristic of a CCD (charge coupled device) camera, orthogonal secondary imaging is carried out on the complex scene before and after the camera rotates, and the nonuniformity of an image is reduced through twice correction; the correction method comprises the following specific processes:
Step 1: inputting image data of a yaw imaging mode to obtain a gray matrix of the yaw imaging data, intercepting an imaging area of a sensor, calculating the degree of a connecting line included angle in an actual yaw radiometric calibration image by using an LSD (line Segment detector) linear detection algorithm, and performing specified processing on the yaw radiometric calibration data according to a detection result of the included angle of the yaw radiometric calibration data to ensure that each line of data in the image is imaging data of all probe elements of the sensor to the same ground object;
step 2: using the data in the step 1, carrying out multi-point curve fitting on the imaging elements of the probe elements by a least square method, solving the non-uniformity correction coefficient of each probe element in each array of the focal plane, and correcting the conventional imaging mode image by using the non-uniformity correction coefficient;
and step 3: and (3) carrying out multipoint curve fitting on the adjacent array splicing pixels by using the corrected image obtained in the step (2) through a least square method, solving a non-uniformity correction coefficient between focal plane arrays, and correcting the image by using the coefficient.
2. The on-orbit nonuniformity correction method facing the mechanical staggered splicing type camera according to claim 1, wherein the step 2 specifically comprises:
Step 2.1, solving the gray level average value of each row of pixels by using the yaw imaging data specified in the step 1 to obtain a row of pixel average value data;
step 2.2, taking each line of data, and calculating a conversion coefficient between the line of data and pixel average value data by using a least square method, wherein the coefficient is a non-uniformity correction coefficient; and finally, correcting the image in the conventional imaging mode by using the correction coefficient.
3. The on-orbit nonuniformity correction method facing the mechanical staggered splicing type camera according to claim 1, wherein the step 3 specifically comprises:
step 3.1, taking an overlapped part image group from the conventional imaging mode image after the first correction;
and 3.2, performing certain translation on the front row and the rear row of array imaging during splicing, wherein the translation distance is determined by the design of a specific camera focal plane. After the data of each image group are aligned in a translation mode, taking out N lines of data groups in the middle of each image group;
and 3.3, solving a conversion coefficient among the data groups by using a least square method, wherein the coefficient is a non-uniformity correction coefficient among the CCD arrays, and finally performing secondary correction on the conventional imaging mode image by using the correction coefficient.
4. The on-track nonuniformity correction method of claim 1, wherein in step 1,
The stipulation of the yaw radiometric calibration data specifically comprises the following steps:
in the formula, the following components are mixed; DN (i, j) represents the gray value of the image at j column of ith row specified by the yaw data; DNSSDefining an image gray value before quantization for the yaw radiometric calibration image; and theta is the actual included angle of the yaw image.
5. The on-track nonuniformity correction method of claim 2, wherein in said step 2,
solving the correction coefficient by using a least square method to make a row of pixel gray values formed by a certain probe element to be corrected be { x }i1,2, r, the gray level mean value of each row of pixels formed by each probe element is listed as { y {i|i＝1,2,...,r}，xi,yiComposing a set of discrete points in a plane (x)i,yi) And (i) 1,2, a., r, performing multi-point curve fitting on the discrete point set by using the following formula, wherein each coefficient of the fitting curve is a correction coefficient.
Linear fitting in linear form y ═ a0+a1x, the formula for solving the coefficients is:
a is a to a quadratic form fitting curve y0+a1x+a2x2The formula for solving the coefficients is:
in the formula, r is the number of discrete points; { a0,a1,...,anThe coefficients of the fitted curve terms are.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010350911.2A CN111862227B (en) | 2020-04-28 | 2020-04-28 | On-orbit non-uniformity correction method of mechanical staggered spliced camera based on complex scene |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010350911.2A CN111862227B (en) | 2020-04-28 | 2020-04-28 | On-orbit non-uniformity correction method of mechanical staggered spliced camera based on complex scene |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111862227A true CN111862227A (en) | 2020-10-30 |
| CN111862227B CN111862227B (en) | 2024-04-12 |
Family
ID=72984940
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010350911.2A Active CN111862227B (en) | 2020-04-28 | 2020-04-28 | On-orbit non-uniformity correction method of mechanical staggered spliced camera based on complex scene |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111862227B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114125431A (en) * | 2021-11-22 | 2022-03-01 | 北京市遥感信息研究所 | Non-uniformity calibration correction method for static track optical large-area array camera |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101515987A (en) * | 2008-12-30 | 2009-08-26 | 中国资源卫星应用中心 | Method for radiometric correction of remote sensing image taken by rotary scan multiple parallel-scan infrared camera |
| US20100329583A1 (en) * | 2009-06-24 | 2010-12-30 | Whiteside Randel S | Non-uniformity error correction with a bilateral filter |
-
2020
- 2020-04-28 CN CN202010350911.2A patent/CN111862227B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101515987A (en) * | 2008-12-30 | 2009-08-26 | 中国资源卫星应用中心 | Method for radiometric correction of remote sensing image taken by rotary scan multiple parallel-scan infrared camera |
| US20100329583A1 (en) * | 2009-06-24 | 2010-12-30 | Whiteside Randel S | Non-uniformity error correction with a bilateral filter |
Non-Patent Citations (1)
| Title |
|---|
| 朱宏殷;郭永飞;司国良;: "多TDICCD拼接相机成像非均匀性实时校正的硬件实现", 光学精密工程, no. 12, 15 December 2011 (2011-12-15) * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114125431A (en) * | 2021-11-22 | 2022-03-01 | 北京市遥感信息研究所 | Non-uniformity calibration correction method for static track optical large-area array camera |
| CN114125431B (en) * | 2021-11-22 | 2023-06-23 | 北京市遥感信息研究所 | Non-uniformity calibration correction method for stationary track optical large area array camera |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111862227B (en) | 2024-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8558899B2 (en) | System and method for super-resolution digital time delay and integrate (TDI) image processing | |
| CN106815805A (en) | Rapid distortion bearing calibration based on Bayer images | |
| CN109903227B (en) | Panoramic image splicing method based on camera geometric position relation | |
| CN105825475B (en) | 360 degree of full-view image generation methods based on single camera | |
| CN102326380B (en) | There are image sensor apparatus and the method for the efficient lens distortion calibration function of row buffer | |
| JP5351195B2 (en) | Solid-state imaging device and portable information terminal | |
| US8531558B2 (en) | Image processing apparatus, image processing method and electronic equipment | |
| US8891899B2 (en) | Methods, systems and apparatuses for pixel value correction using multiple vertical and/or horizontal correction curves | |
| CN110120077B (en) | Area array camera in-orbit relative radiation calibration method based on satellite attitude adjustment | |
| CN110501025B (en) | On-orbit calibration method of rolling shutter area array CMOS camera | |
| EP4202822A1 (en) | Image processing method, image processing system, electronic device, and readable storage medium | |
| CN115239820A (en) | Split type flying vehicle aerial view real-time splicing and parking space detection method | |
| CN105869129B (en) | For the thermal infrared images residue non-uniform noise minimizing technology after nonuniformity correction | |
| CN111862227B (en) | On-orbit non-uniformity correction method of mechanical staggered spliced camera based on complex scene | |
| CN112465915A (en) | Vehicle-mounted panoramic system calibration method | |
| CN108898565B (en) | Inverse transformation method for geometrical distortion reduction of TDI CCD camera swing scanning imaging image | |
| US11457202B2 (en) | Imaging device | |
| CN114125431A (en) | Non-uniformity calibration correction method for static track optical large-area array camera | |
| CN112258581A (en) | On-site calibration method for multi-fish glasses head panoramic camera | |
| CN108596852B (en) | Object image mapping reduction method for large attitude angle imaging mirror image geometric distortion of area-array camera | |
| CN115086550B (en) | Meta imaging system | |
| CN116188278A (en) | Real-time information enhancement method on high-resolution uncooled infrared multispectral camera line and application thereof | |
| CN113379648B (en) | High-resolution seven-number and resource three-number stereoscopic image joint adjustment method | |
| CN110580692B (en) | Method for correcting radiation consistency of multi-line time difference scanning image | |
| CN107945104A (en) | A kind of method for panoramic imaging based on space virtual reality camera |
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 |