CN104143187A - Method for registering sub-pixel images through multi-linear-array time difference scanning expansion sampling - Google Patents
Method for registering sub-pixel images through multi-linear-array time difference scanning expansion sampling Download PDFInfo
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- CN104143187A CN104143187A CN201410319202.2A CN201410319202A CN104143187A CN 104143187 A CN104143187 A CN 104143187A CN 201410319202 A CN201410319202 A CN 201410319202A CN 104143187 A CN104143187 A CN 104143187A
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Abstract
The invention provides a method for registering sub-pixel images through multi-linear-array time difference scanning expansion sampling. The method includes the steps that (1) a multi-linear-array time difference scanning detection device is constructed; (2) a plurality of linear array detectors conduct imaging on the same position in a view field in sequence, and the step (3) is conducted immediately after imaging is completed; or each linear array detector conducts scanning imaging in the scanning direction according to a sampling interval corresponding to the sampling frequency set in the step (1), Nt groups of image data are obtained through each time of imaging, and the step (3) is conducted immediately; (3) the Nt groups of image data of each linear array detector are processed to form a frame detection image; (4) the frame detection images obtained by the linear array detectors correspondingly are spliced to obtain the two sub-pixel images; (5) non-uniformity correction is conducted on the two sub-pixel images respectively; (6) the sub-pixel image which is formed firstly is used as a standard, the sub-pixel image which is formed later is moved forwards by Lp lines in the scanning direction; (7) the affine transformation coefficients of the two sub-pixel images are obtained, and matching of the two sub-pixel images is completed through the coefficients.
Description
Technical field
The invention belongs to image processing field, relate to a kind of multi-thread row moveout scan expansion sampling subpixel image method for registering.
Background technology
At present, the mode of existing raising image resolution ratio is varied, specifically has following several mode: CCD improves to picture receiver, dwindles picture dot size, dwindles inter-pixel distance, improves picture dot number etc., but due to the impact of existing improving technology finite sum quantum efficiency, be difficult to break through; Utilize software directly single image to be carried out to difference, the method does not increase the quantity of information of error image, so, not from improving in essence the resolution of image; Utilize micro lens technology and pupil resolving power technology can cause the excessive drawback of system bulk; In general, cost that prior art is difficult to overcome is high, volume large, implement the deficiencies such as difficulty is large, under some occasion, cannot meet the needs that further develop.And for interframe registration technology, because detector is across the impact such as picture dot and noise, even if registration technology is very ripe, all can be subject to the impact that single-frame images resolution is low, and make registration accuracy deficiency, finally make that detection of a target precision is lower, difficulty is larger, so, seek a kind of raising single-frame images resolution and coordinate suitable method for registering, thereby the technology that late detection aimed at precision is made moderate progress is very necessary.
Summary of the invention
Technology of the present invention is dealt with problems and is: overcome the deficiencies in the prior art, propose a kind of multi-thread row moveout scan expansion sampling subpixel image method for registering, solve the registration problems of two free poor width detection images.
One of technical solution of the present invention is: a kind of multi-thread row moveout scan expansion sampling subpixel image method for registering, and step is as follows:
(1) construct multi-thread row moveout scan expansion sampling sniffer, this device comprises optical system, scanning mechanism and multi-thread row detector; Described scanning mechanism comprises pendulum mirror and drive shaft thereof; Described multi-thread row detector is two-wire row detector, and detector array adopts N
tindividual detection array composition, the instantaneous field of view that pixel is corresponding is IFOV, adjacent two detection arrays are arranged in parallel, at the vertical scanning direction 1/N that staggers successively
tindividual pixel, and the detection array S that samples in direction of scanning, in a sampling length is set
tinferior; Described sampling length is the instantaneous field of view that pixel is corresponding; Described N
tbe more than or equal to 2; Described S
tspan is S
t>=2;
(2) optical system images in focal plane by scene in visual field together with scanning mechanism, drive shaft drives the rotation of pendulum mirror, scene imaging in linear field is with tandem two detector array on the inswept focal plane of certain speed, two detector array are to successively imaging of same position scene in visual field, imaging time interval
each detector array adopts expansion sample mode to carry out imaging, i.e. N in each detector array
tthe imaging simultaneously of individual detection array, obtains N
tgroup view data; Proceed to immediately afterwards step (3); Each detector array carries out scanning imagery according to the sampling interval that sampling number is corresponding is set in step (1) in direction of scanning, each imaging obtains respectively N
tgroup view data, obtains proceeding to immediately step (3) after data;
Above-mentioned, distance d between two detector array, optical system focal distance f, the angular scanning speed of scanning mechanism is ω;
(3) respectively by the N of two detector array
tgroup view data is alignd after splicing is processed and is formed a frame detection image;
(4) on direction of scanning, complete after default sampling number, the frame detection image that each detector array correspondence is obtained spliced and obtains two width subpixel images according to the time;
(5) two width subpixel images are carried out to Nonuniformity Correction;
(6) taking subpixel image corresponding to the detector array of formerly imaging as benchmark, the subpixel image corresponding detector array of rear imaging is moved forward in direction of scanning
oK, L
pround numbers row, detector array array pixel dimension is a × a;
(7) selected characteristic point from two width subpixel images after treatment, and carry out characteristic matching, to asking for the affined transformation coefficient of two width images, utilize this coefficient to complete the coupling of two width images according to matching characteristic point.
Nonuniformity correction in described step (5) adopts the synthetic mode of proofreading and correct of multi-thread row moveout scan image, and detailed process is as follows:
(5.1) two width subpixel images are intersected to splicing by row, form the new stitching image I of a width
p1;
(5.2) to stitching image I
p1each row image carry out Nonuniformity Correction, all row obtain row to the image I after nonuniformity correction after finishing dealing with
p2;
(5.3) according to the order of the row intersection splicing of two width images in step (5.1), from I
p2middlely extract respectively corresponding row image, rebuild two width and complete the subpixel image of row to Nonuniformity Correction;
(5.4) by complete row to two width subpixel images after nonuniformity correction by same direction half-twist respectively, repeating step (5.1)~(5.3), obtain proofreading and correct rear image I
p3;
(5.5) according to the order of the row intersection splicing of two width images in step (5.1), from I
p3middlely extract respectively corresponding row image, rebuild two width and complete the subpixel image of row to nonuniformity correction;
(5.6) by completing the capable two width subpixel images to nonuniformity correction by 90 ° of the opposite spins of step (5.4) rotation, two width subpixel images of row, column both direction nonuniformity correction have been obtained.
Described step (7) can also adopt following step to substitute, and adopts sub-pix image registration techniques to mate.
The angular scanning speed of described multi-thread row moveout scan detector scanning mechanism is
the target minimum movement speed v of wherein surveying
min, the ground sampled distance GSD of detector array.
The present invention's advantage is compared with prior art:
1, the present invention utilizes N
tthe detection array composition detector array of individual Heterogeneous Permutation, realizes the two-dimensional expansion of target context in length and width direction by expansion sample mode, is conducive to improve the precision of coupling.
2, because the explorer response of multi-thread row detector is inconsistent, cause two images that alignment becomes to exist overall intensity poor, the present invention adopts the synthetic mode of proofreading and correct of multi-thread row moveout scan image, can effectively reduce the gray scale difference between alignment image, make multi-thread row image in same tonal range, can improve the precision of sub-pix coupling.
3, the present invention makes full use of detector array and arranges the imaging mode of feature and setting, taking subpixel image corresponding to the detector array of formerly imaging as benchmark, the subpixel image corresponding detector array of rear imaging is moved forward to L in direction of scanning
poK, carry out two width Rapid Image Registrations, adopt again on this basis a sub-pix method for registering to mate, dwindle two width images match scopes, improve matching efficiency, reduce matching error, improve matching precision.
4, the present invention can be used for solving the Rapid matching of any two alignment images in multi-thread column scan detection system, is follow-up data processing, and background inhibition, target detection etc. provide basis.
Brief description of the drawings
Fig. 1,2 is two kinds of mode schematic diagram of the present invention's multi-thread row moveout scan expansion sampling sniffer;
Fig. 3 is that schematic diagram is processed in detector array two field picture splicing of the present invention;
Fig. 4 is multi-thread row moveout scan subpixel image registration process flow diagram of the present invention;
Embodiment
Below in conjunction with accompanying drawing and example, the present invention is elaborated.A kind of multi-thread row moveout scan expansion sampling subpixel image method for registering, step is as follows:
(1) construct multi-thread row moveout scan expansion sampling sniffer, this device comprises optical system 1, scanning mechanism 2 and multi-thread row detector 3; Described Scan Architecture comprises pendulum mirror and drive shaft thereof; Described multi-thread row detector is two detector array, and detector array adopts N
tindividual detection array composition, the instantaneous field of view that pixel is corresponding is IFOV, adjacent two detection arrays are arranged in parallel, at the vertical scanning direction 1/N that staggers successively
tindividual pixel, and the detection array S that samples in direction of scanning, in a sampling length is set
tinferior; Described sampling length is the instantaneous field of view that pixel is corresponding; The sweep velocity of described multi-thread row moveout scan sniffer scanning mechanism is
wherein distance d between two detector array, the target minimum movement speed v of detection
min, optical system focal distance f, the ground sampled distance GSD of detector array; Described N
tbe more than or equal to 2; Described S
tspan is S
t>=2; Below with N
t=2 describe for example.
What Fig. 1 provided is front end scanning probe device; The incident light of the emittance information that comprises target and background converges to focal plane through optical system 1 after the reflection of pendulum mirror, forms the picture of scenery, and drive shaft drives pendulum mirror according to default angular speed rotation, makes picture inswept each detector array successively of scenery.When the picture of scenery is during with inswept one of them detector array of certain speed, detector is sampled to the picture of scenery.What Fig. 2 provided is rear-end scanning sniffer.The incident light of the emittance information that comprises target and background converges to pendulum mirror through optical system 1, reflexes to focal plane through pendulum mirror, forms the picture of scenery.Drive shaft drives pendulum mirror according to default angular speed rotation, makes picture inswept each detector array successively of scenery.When the picture of scenery is during with inswept one of them detector array of certain speed, detector is sampled to the picture of scenery.
In this example, optical system 1 is the optical system of typical Cassegrain form, formed by primary mirror and secondary mirror, incident ray through primary mirror and secondary mirror reflection after converging, incide on detector array.
(2) optical system 1 together with scanning mechanism 2 by visual field in scene image in focal plane, drive shaft drives the rotation of pendulum mirror, scene imaging in linear field is with tandem two-wire row detector on the inswept focal plane of certain speed, two detector array are to successively imaging of same position scene in visual field, imaging time interval
each detector array adopts expansion sample mode to carry out imaging, i.e. N in each detector array
tthe imaging simultaneously of individual detection array, obtains N
tgroup view data; Obtain entering immediately step (3) after view data; In this simultaneously, each detector array still according in step (1), arrange in a sampling length sampling number, carry out scanning imagery in direction of scanning, each imaging obtains respectively N
tgroup view data, obtains proceeding to immediately step (3) after view data equally; For example, S can be set
t>=2, can realize the more than 2 times over-sampling of detector array on direction of scanning;
(3) respectively by the N of two detector array
tgroup view data is alignd after splicing is processed and is formed a frame detection image, and splicing is processed as shown in Figure 3, by N
tgroup pattern intersects splicing mutually.Processed and obtained sub-pixel frame detection image by splicing, realize target is in the stretching of vertical scanning direction.
(4), after default sampling number, the frame detection image that each detector array correspondence is obtained spliced and obtains two width subpixel images according to the time; Default desirable 200~300 row of sampling number, increase default sampling number and can increase scan image details, improve the precision of successive image processing; Reduce the efficiency that default sampling number can improve data processing, therefore default sampling number can regulate according to actual conditions
(5) respectively two width subpixel images are carried out to Nonuniformity Correction; This step adopts at present conventional image non-uniform correction method, exceeds and is described.
(6) taking subpixel image corresponding to the detector array of formerly imaging as benchmark, the subpixel image corresponding detector array of rear imaging is moved forward in direction of scanning
oK, L
pround numbers row, detector array array pixel dimension is a × a;
(7) selected characteristic point from two width subpixel images after treatment, and carry out characteristic matching, to asking for the affined transformation coefficient of two width images, utilize this coefficient to complete the coupling of two width images according to matching characteristic point.Two width subpixel image registration flow processs are as shown in Figure 4, specific as follows:
(7.11) taking subpixel image corresponding to the detector array of first imaging as reference picture, the subpixel image that the detector array of rear imaging is corresponding is image subject to registration;
(7.12) to reference picture and image subject to registration respectively according to the unique point threshold value extract minutiae of setting, feature point extraction algorithm can adopt general feature point extraction algorithm, as Harris angle point etc.;
(7.13) differentiate the unique point number of extracting in reference picture and image subject to registration, be greater than 3 and proceed to step (7.14), otherwise proceed to step poly-(7.12), adjustment feature point threshold value, again extract minutiae;
(7.14) unique point of reference picture and image subject to registration being extracted is respectively carried out Feature Points Matching, and matching range is got the δ neighborhood of reference picture unique point coordinate, 0≤δ≤4;
(7.15) unique point that judgement has been mated, to whether being greater than 3, is to proceed to frequently rapid (7.16), otherwise proceeds to step poly-(7.12), adjustment feature point threshold value, again extract minutiae;
(7.16) unique point pair obtaining according to step (7.15), asks for affined transformation coefficient by least square method;
(7.17) registration parameter calculating according to (7.16), treats registering images and carries out image conversion, obtains the image after registration;
Step (7) can also adopt following step to substitute, and adopts sub-pix image registration algorithm to mate, specific as follows:
(7.21) taking subpixel image corresponding to the detector array of first imaging as reference picture, the subpixel image that the detector array of rear imaging is corresponding is image subject to registration;
(7.22) in reference picture, search for gradient largest block; Gradient largest block is defined as: the gradient image of computing reference two field picture, and pixel the logical value corresponding gradient that is greater than image gradient maximal value 4/5 is labeled as to 1, otherwise is labeled as 0, the image of formation is called logical value image.Select suitably big or small window at logical value image slide, be called gradient largest block containing 1 maximum piece corresponding to window.Determine the position of gradient largest block by the maximal value in comparison moving window.Window size is set up and is adopted 50x50;
(7.23) be to picture to the gradient largest block in (7.22), adopt based on the relevant image matching algorithm of gray scale, carry out reference picture and mate with the sub-pix of image subject to registration.Obtain more intensive grid and supply target image search by reference picture being carried out to interpolation, obtain the registration accuracy of sub-pixel;
(7.24) registration parameter calculating according to (7.23), treats registering images and carries out image conversion, obtains the image after registration.
The unspecified part of the present invention belongs to general knowledge as well known to those skilled in the art.
Claims (4)
1. a multi-thread row moveout scan expansion sampling subpixel image method for registering, is characterized in that step is as follows:
(1) construct multi-thread row moveout scan expansion sampling sniffer, this device comprises optical system, scanning mechanism and multi-thread row detector; Described scanning mechanism comprises pendulum mirror and drive shaft thereof; Described multi-thread row detector is two detector array, and detector array adopts N
tindividual detection array composition, the instantaneous field of view that pixel is corresponding is IFOV, adjacent two detection arrays are arranged in parallel, at the vertical scanning direction 1/N that staggers successively
tindividual pixel, and the detection array S that samples in direction of scanning, in a sampling length is set
tinferior; Described sampling length is the instantaneous field of view that pixel is corresponding; Described N
tbe more than or equal to 2; Described S
tspan is S
t>=2;
(2) optical system images in focal plane by scene in visual field together with scanning mechanism, drive shaft drives the rotation of pendulum mirror, scene imaging in linear field is with tandem two detector array on the inswept focal plane of certain speed, two detector array are to successively imaging of same position scene in visual field, imaging time interval
each detector array adopts expansion sample mode to carry out imaging, i.e. N in each detector array
tthe imaging simultaneously of individual detection array, obtains N
tgroup view data; Proceed to immediately afterwards step (3); Each detector array carries out scanning imagery according to the sampling interval that sampling number is corresponding is set in step (1) in direction of scanning, each imaging obtains respectively N
tgroup view data, obtains proceeding to immediately step (3) after data;
Above-mentioned, distance d between two detector array, optical system focal distance f, the angular scanning speed of scanning mechanism is ω;
(3) respectively by the N of two detector array
tgroup view data is alignd after splicing is processed and is formed a frame detection image;
(4) on direction of scanning, complete after default sampling number, the frame detection image that each detector array correspondence is obtained spliced and obtains two width subpixel images according to the time;
(5) two width subpixel images are carried out to Nonuniformity Correction;
(6) taking subpixel image corresponding to the detector array of formerly imaging as benchmark, the subpixel image corresponding detector array of rear imaging is moved forward in direction of scanning
oK, L
pround numbers row, detector array array pixel dimension is a × a;
(7) selected characteristic point from two width subpixel images after treatment, and carry out characteristic matching, to asking for the affined transformation coefficient of two width images, utilize this coefficient to complete the coupling of two width images according to matching characteristic point.
2. the multi-thread row moveout scan expansion of one according to claim 1 sampling subpixel image method for registering, it is characterized in that: the nonuniformity correction in described step (5) adopts the synthetic mode of proofreading and correct of multi-thread row moveout scan image, and detailed process is as follows:
(5.1) two width subpixel images are intersected to splicing by row, form the new stitching image I of a width
p1;
(5.2) to stitching image I
p1each row image carry out Nonuniformity Correction, all row obtain row to the image I after nonuniformity correction after finishing dealing with
p2;
(5.3) according to the order of the row intersection splicing of two width images in step (5.1), from I
p2middlely extract respectively corresponding row image, rebuild two width and complete the subpixel image of row to Nonuniformity Correction;
(5.4) by complete row to two width subpixel images after nonuniformity correction by same direction half-twist respectively, repeating step (5.1)~(5.3), obtain proofreading and correct rear image I
p3;
(5.5) according to the order of the row intersection splicing of two width images in step (5.1), from I
p3middlely extract respectively corresponding row image, rebuild two width and complete the subpixel image of row to nonuniformity correction;
(5.6) by completing the capable two width subpixel images to nonuniformity correction by 90 ° of the opposite spins of step (5.4) rotation, two width subpixel images of row, column both direction nonuniformity correction have been obtained.
3. the multi-thread row moveout scan expansion of one according to claim 1 sampling subpixel image method for registering, is characterized in that: described step (7) can also adopt following step to substitute, and adopts sub-pix image registration techniques to mate.
4. the multi-thread row moveout scan expansion of one according to claim 1 sampling subpixel image method for registering, is characterized in that: the angular scanning speed of described multi-thread row moveout scan sniffer scanning mechanism is
wherein, the target minimum movement speed v of detection
min, the ground sampled distance GSD of detector array.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2009026522A1 (en) * | 2007-08-23 | 2009-02-26 | Lockheed Martin Corporation | Multi-bank tdi approach for high-sensitivity scanners |
CN101706961A (en) * | 2009-11-10 | 2010-05-12 | 北京航空航天大学 | Image registration method and image registration device |
US20110115793A1 (en) * | 2009-11-16 | 2011-05-19 | Grycewicz Thomas J | System and Method for Super-Resolution Digital Time Delay and Integrate (TDI) Image Processing |
CN102708546A (en) * | 2012-05-09 | 2012-10-03 | 中国科学院上海技术物理研究所 | Common-light path multi-module spliced focal plane image non-uniformity correction method |
CN103268599A (en) * | 2013-04-19 | 2013-08-28 | 中国科学院长春光学精密机械与物理研究所 | Multi-linear-array charge coupled device (CCD) sub-pixel staggered imaging super-resolution reconstruction method |
-
2014
- 2014-07-04 CN CN201410319202.2A patent/CN104143187B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2009026522A1 (en) * | 2007-08-23 | 2009-02-26 | Lockheed Martin Corporation | Multi-bank tdi approach for high-sensitivity scanners |
CN101706961A (en) * | 2009-11-10 | 2010-05-12 | 北京航空航天大学 | Image registration method and image registration device |
US20110115793A1 (en) * | 2009-11-16 | 2011-05-19 | Grycewicz Thomas J | System and Method for Super-Resolution Digital Time Delay and Integrate (TDI) Image Processing |
CN102708546A (en) * | 2012-05-09 | 2012-10-03 | 中国科学院上海技术物理研究所 | Common-light path multi-module spliced focal plane image non-uniformity correction method |
CN103268599A (en) * | 2013-04-19 | 2013-08-28 | 中国科学院长春光学精密机械与物理研究所 | Multi-linear-array charge coupled device (CCD) sub-pixel staggered imaging super-resolution reconstruction method |
Non-Patent Citations (2)
Title |
---|
ZHEN-HUI HU ET AL: "A Sub-Pixel Image Registration Technique with Applications to Defect Detection", 《INTERNATIONAL JOURNAL OF COMPUTER, ELECTRICAL, AUTOMATION, CONTROL AND INFORMATION ENGINEERING》 * |
金伟其 等: "扫描型焦平面热成像系统的亚像元处理算法研究", 《红外与毫米波学报》 * |
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