CN102881029A - Compression and reconstruction method for thermal wave image sequence - Google Patents
Compression and reconstruction method for thermal wave image sequence Download PDFInfo
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- CN102881029A CN102881029A CN2012102565958A CN201210256595A CN102881029A CN 102881029 A CN102881029 A CN 102881029A CN 2012102565958 A CN2012102565958 A CN 2012102565958A CN 201210256595 A CN201210256595 A CN 201210256595A CN 102881029 A CN102881029 A CN 102881029A
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Abstract
The invention relates to a compression and reconstruction method for efficiently fixing viewing field pulse thermal wave image sequence and belongs to the field of equipment thermal wave imaging nondestructive detection techniques. Aiming to solve the colossal data processing quantity problem of the infrared thermal wave image sequence, the method comprises the following steps: a thermal wave pixel point data sequence heat conduction law and a sequence partition method are adopted to classify the data sequences so as to generate a corresponding representative sequence and a category table; according to a one-dimension thermal wave temperature attenuation model and a multinomial data fitting method, a fitting coefficient table of all category sequences is obtained; thermal image acquisition parameters, and the data of both the fitting coefficient table and the category table are adopted as the compression characteristic of the thermal wave image sequence, so as to form a thermal wave image compression document for storage; and the fitting coefficients are adopted to rebuild the thermal wave image sequence according to the category table. According to the invention, the category number can be flexibly set according to practical detection requirements; the ratio of compression can reach more than ten thousand times, and the calculation quantity is reduced by thousand times; and the requirement on computer hardware is remarkably reduced. The method is flexible in use, is particularly suitable for large-viewing field thermal image processing, and has an extensive application prospect.
Description
Technical field
The invention belongs to technical field of image processing, relate to heat wave Non-Destructive Testing image processing method, particularly a kind of high efficiency compression and reconstructing method of fixedly visual field pulse heat wave image sequence.
Background technology
Infrared thermal wave (Thermal Wave) Dynamic Non-Destruction Measurement is a kind of novel Dynamic Non-Destruction Measurement that is risen by US Airways space flight and national defence field eighties of last century nineties.Since nineteen ninety, actively develop the research of heat wave theory and technology abroad, along with improving constantly of computer level and thermal infrared imager precision, this technology has had increasingly extensive application in fields such as Aero-Space, petrochemical complex, building, electric power, medical science at present.The theoretical foundation of thermal wave detection technology is heat wave theory of conduction and thermal radiation law, and the emphasis of research is the interaction between variability thermal source (such as cycle, pulse, step function thermal source etc.) and detected object and the geometry thereof.After being heated, the transmission that the physical structural characteristic that different material surfaces and surface are following and boundary condition will affect heat wave and the change of temperature field that will affect material surface.By controlling the thermal excitation method and utilizing the change of temperature field on thermal imaging system detecting material surface and the special gordian techniquies such as thermal imagery sequential treatment technique to carry out Non-Destructive Testing.It detects principle as shown in Figure 1.
In the thermal imagery sequential treatment technique, because high frame frequency thermal-image data amount is huge, must compress and reconstruction process, in order to use other algorithm to carry out defects detection and identification, so the compression of heat wave image and reconstruction are one of the most basis in the heat wave Non-Destructive Testing and crucial technology.According to statistics, existing more than 30～40 kind of Image Compression Coding Algorithm emerges at present, and wherein the standards such as the AVI of comparative maturity, MPEG can be used.But these algorithms are not owing to taking full advantage of the character of heat wave itself, and its ratio of compression is difficult to reach the requirement of heat wave Non-Destructive Testing.At present, the Steven M.Shepard of U.S. Thermal Wave Imaging (TWI) company has done a large amount of work in this respect, has proposed original image reconstruction theoretical (TSR), has grasped the gordian technique of thermographic compression storage.Domestic, the gold ten thousand equality people of the people such as the Zhang Cunlin of the people such as the Yang Danggang of the people such as the Guo Xingwang of BJ University of Aeronautics ﹠ Astronautics, Beijing Research Inst. of Aeronautic Material, Capital Normal University and Beijing Wei Taikai letter technology company limited utilize pulse heat motivational techniques and external import heat wave nondestructive detection system equipment, carried out correlative study, its basic theory and gordian technique were carried out exploratory development.But in recent years, rapid raising along with high precision thermal imaging system precision, speed and spatial resolution, 640 * 480 and 1024 * 768 contour pixel thermal imaging systems progressively come into operation, also need 20～30 second computing time (320 * 240 pixels such as U.S. TWI need server as process computer) that originally external spatial resolution is less, now as still adopt original algorithm and server, the time that image is processed is original 4 times and 8 times.Obviously, this is difficult to the requirement of the heat wave Non-Destructive Testing in satisfied scene and laboratory, therefore must do improvement and bring new ideas in Processing Algorithm.
In sum, up to the present, find that not yet a kind of simple method can realize infrared thermal wave NDT compression of images and reconstruction, with fast detecting and the identification of satisfied defective.
Summary of the invention
For above-mentioned prior art situation, the object of the present invention is to provide a kind of high-level efficiency fixedly compression and the reconstructing method technical method of visual field pulse heat wave image sequence.
Compression and the reconstructing method of a kind of heat wave image sequence of the present invention is characterized in that: may further comprise the steps:
Step 1: obtain test specimen heat wave image sequence with pulse heat wave method, use heat wave pixel data sequence thermal conductivity law and sequence sorting technique, data sequence is divided into type about 100～200, generate and represent sequence accordingly, and thermal imagery all sequences position is numbered and registered type, generate the classification table;
Step 2: according to one dimension heat wave temperature model and polynomial data fitting algorithm, all are represented the least square fitting that sequence is unified exponent number, obtain the fitting coefficient table of all categories sequence; Unified exponent number is generally got five rank;
Step 3: with thermal imagery acquisition parameter, fitting coefficient table data and the classification table data compressive features as the heat wave image sequence, arrange one by one and generate the one-dimensional data sequence, preserve with binary floating point logarithmic data form, form the heat wave compressed document image, finish compression of images and Computer Storage;
Step 4: use fitting coefficient table and five rank polynomial expression normalized forms, generate the constant duration sequence according to sampling parameter, substitution polynomial expression normalized form rebuilds and reduces that all represents sequence, according to classification table reconstruction heat wave image sequence.
The present invention further provides a kind of compression and reconstructing method of heat wave image sequence, it is characterized in that: heat wave pixel data sequence thermal conductivity law satisfies shown in formula (1) in the described step 1:
Be the material of h for thickness in the formula, under the effect of heat pulse q, ρ is density of material, and c is material specific heat, (schematic diagram as shown in Figure 2), T (0, t) be measured surface temperature change with time model, its defectiveness and zero defect place are owing to the reflection of heat wave flow field at fault location, and its drop in temperature curve has obvious difference, and along with the propelling of time, its defect information shows as the temperature field at the heat wave image and distributes.
Step 1.1: according to this rule, this method is chosen wherein one section the most obvious continuous 5-10 of defective constantly thermal imagery gray-scale value (infrared radiation density strength value) weighted sum, as its equidistant classification foundation; Or choose wherein one section the most obvious continuous 5-10 of defective moment thermal imagery gray-scale value, utilize the classification of K average Dynamic Clustering Algorithm; Or the gray-scale value of the most obvious certain the frame thermal imagery of selection defective is as equidistant classification foundation.Classification is several to be arranged according to needs, generally selects n=100～200 to get final product;
Step 1.2: after the classification, select the equal value sequence of the center sequence of each class or several center sequences as representing sequence S
i, i=1,2 ..., n, and all pixel sequence locations of thermal imagery are numbered and registered type, classification table S generated.
The present invention further provides a kind of compression and reconstructing method of heat wave image sequence, it is characterized in that: the data fitting method in the described step 2 represents sequence S for all
i, i=1,2 ..., n, and the rule of formula (1) carry out least square fitting, specifically are divided into following a few step:
Step 2.1: eliminate basic infrared emanation.Data sequence about front 18 frames of flash of light is averaged, obtain basal heat radiation m
i, then from representing sequence S
iDeduct basic radiation, obtain new representative sequence
Step 2.2: extract and effectively represent sequence.Find first sequence maximum value position t
m, the position of namely glistening, then take this point as starting point, with thereafter time series data as effectively representing sequence
Reset again data length p=n-t
m+ 1, and rise time Variables Sequence t
i=1,2 ..., p};
Step 2.3: carry out polynomial data fitting.To the time variable sequence with effectively represent sequence and carry out respectively log-transformation, then unified 5 rank polynomial expressions (seeing formula (2)) and the residual error of adopting controlled level, to two least square data fittings that Number Sequence carried out non-equidistance, obtain corresponding fitting coefficient C
i={ c
I0, c
I1..., c
I5;
y
i＝c
i0+c
i1t+c
i1t
2+…+c
i5t
5，i＝1，2，...，n (2)
The present invention further provides a kind of compression and reconstructing method of heat wave image sequence, it is characterized in that: thermal imagery acquisition parameter P mainly contains four in the described step 3, is respectively to adopt frame number, employing frame frequency, thermal imagery width and thermal imagery height;
Step 3.1: specific practice is with thermal imagery acquisition parameter P, fitting coefficient table C
iData and classification table S data are arranged its data vector one by one as the compressive features of heat wave image sequence, and namely one by one, separator is not stayed in the centre, generate the one-dimensional data sequence;
Step 3.2: then use binary floating point logarithmic data form, in computing machine, create a user-defined file and preserve, form the heat wave compressed document image, finish compression of images and Computer Storage;
The present invention further provides a kind of compression and reconstructing method of heat wave image sequence, it is characterized in that: in described step 4, use fitting coefficient table C
iWith polynomial expression normalized form (2), according to time variable sequence t
i=1,2 ..., and the p} logarithmic form rebuilds and reduces that all represents sequence for people's polynomial expression normalized form, and attention will be done exponent arithmetic one time to each data here, reduces original temperature changing regularity; According to the classification table, rebuild the heat wave image sequence with reduction representative sample data sequence at last;
The present invention further provides a kind of compression and reconstructing method of heat wave image sequence, it is characterized in that: the classification number can detect needs according to reality and arrange flexibly, the thermal-image data of a general 1000-2000 frame, its each pixel, be compressed at last in 6 parameters, its longitudinal compression is than being 167-334; The thermal imagery of 640 * 480=307200 or 1024 * 768=786432 point pixel is arranged for every frame, as be compressed into 200 and represent sequence, its horizontal compression ratio can reach 1536 or 3932 so, and overall compression ratio reaches more than 256512 to 1313288 times.
The inventive method is compared with prior art, has reduced ten hundreds of repetition matches, and calculated amount sharply reduces, and algorithm speed significantly improves, and computer hardware is required obviously to reduce.The method is used flexibly, to improving the thermal imagery treatment effeciency special effect is arranged, and is particularly suitable for the fast processing of large visual field thermal imagery and engineering site, has broad application prospects and promotional value.Moreover, the method can also be drifted at fluorescence field microscopy images, phosphorescence field microscopy images and picture the fields such as micro-image processing and is applied.
Description of drawings
Fig. 1: thermal wave detection system chart of the present invention
Fig. 2: template test specimen heat-conduction principle figure
Fig. 3: defect area and a non-defect area picture number temperature-time changes comparison diagram
Fig. 4: test specimen front view (FV) in kind
Fig. 5: test specimen back view in kind
Fig. 6: the extraction characteristic frame is also classified
Fig. 7: represent the sequence multinomial fit procedure
Fig. 8: single pixel temperature radiation time series signal B and match signal C comparison diagram thereof
Fig. 9: single-point reproducing sequence figure
Figure 10: original the 35th frame thermography
Figure 11: rear the 35th frame thermography of reduction is processed in the single frames classification
Figure 12: single frames is the 35th frame thermography behind fitting reconfiguration
Figure 13: the 35th frame thermography after the multiframe classification is processed
Figure 14: multiframe is the 35th frame thermography behind fitting reconfiguration
Figure 15: the 35th frame thermography after the classification of K average is processed
Figure 16: the K average is the 35th frame thermography behind fitting reconfiguration
Embodiment
The present invention will be described in detail below in conjunction with drawings and Examples:
Embodiment:
At first be implemented as follows according to step 1:
(1) obtain the heat wave image, as shown in Figure 1, pulse heat is made of thermal imaging system, computing machine, display, power supply and thermal excitation source as the pick-up unit of method.In testing process, the thermal excitation signal is sent in the thermal excitation source, and detected object is carried out transient heating, gather the distributed intelligence of measurand surface temperature field on time and space by thermal imaging system, consist of the heat wave image sequence, sequential value is corresponding point infrared radiation density, can be converted into temperature value.The as calculated machine compression of thermal imagery sequence, preservation, reconstruct and other processing means are analyzed, and the defect information that obtains is directly exported by display at last.
(2) principle of thermal imagery Changing Pattern as shown in Figure 2, under the heat pulse heating condition, is the material of h for thickness, under the effect of heat pulse q, and can be in the hope of the test specimen temperature:
Wherein, r is the hot reflection coefficient of defective, in general, is assumed to be total reflection (r=1), so at material surface x=0 place, the temperature field distribution function is:
First is hot-fluid cooling item in time in the formula, second be heat wave at the n of material internal secondary reflection, when reflexing to material surface, propagated the distance of 2nh.Because the attenuation ratio of heat wave is very fast, so can ignore the high secondary reflection item of n＞1, obtains:
(3) thermal imagery Changing Pattern as shown in Figure 3, is the temperature time history plot on defect area surface and non-defect area surface certain a bit, and as seen from the figure, the temperature of model surface raises rapidly after PULSE HEATING, afterwards gradually cooling.In cooling procedure, the change procedure of defect area surface temperature is different from non-defect area surface temperature change procedure.In actual testing process, be exactly on this basis, finish that the quantitative and qualitative analysis of defective detects.
(4) embodiment detected object, shown in Fig. 4,5, be experiment test specimen positive and negative figure in kind, material for test is the metallic steel housing, long 280mm, wide 200mm, thick 6mm, the back side is processed with the debonding defect of 8 flat hole simulations, and four flat holes, top degree of depth is all 1mm, and diameter is respectively 5mm, 10mm, 16mm, 20mm; Four the flat hole dias in below are all 20mm, and the degree of depth is respectively 2mm, 3mm, 4mm, 5mm.
(5) select characteristic frame to classify, be illustrated in figure 6 as test specimen applied transient heat excitation after, thermal imaging system collects and amounts to 550 * 300 1000 frame thermal imagerys, then according to thermal imagery temperature damping rule, therefrom extract the 3-5 frame, such as 35-38 frame thermography as basis of classification.As with after this 5 frame weighted mean, equidistantly be divided into 200 classes by the thermal imagery gray-scale value.The thermal imagery of so original 550 * 300=165000 pixel of 1000 frames has become L=[S
1, S
2..., S
200], totally 200 time series (each sequence S that represent class
i=[s
I1, s
I2..., s
I1000], 1000 data are arranged) and a classification table S who comprises each location of pixels and classification information thereof.
Be implemented as follows according to step 2:
(1) represents 5 rank fitting of a polynomials of sequence with Fig. 7 logical process, obtain 200 all 1200 fitting coefficients that represent sequence.
(2) Fig. 8 is the comparison diagram that certain represents the single pixel temperature radiation time series original signal B of sequence and match signal C thereof, and Fig. 9 is single-point reproducing sequence figure.
Be implemented as follows according to step 3:
According to step 3 correlation parameter is preserved into the thermal imagery compressed file, its data layout is as follows
File type: double-precision quantity; DataFile:File of double;
File layout: be stored in one by one in the data file by following form, note not having sequence number in the file, also do not have blank character between data.
1: totalframes maxzhen
2: thermal imagery height rxgao
3: thermal imagery width rxkuan
4: sampling interval Dt
5: fitting coefficient table C
iData, totally 200 * 6=1200
6: classification table S data, rxkuan * rxgao=550 * 300=165000 altogether, according to every frame thermal imagery from left to right, serial number from top to bottom, namely 1,2 ..., 165000, its type number 1,2 of the data recording of each location of pixels ..., 200.
These routine compressed file data are respectively
1000.0 300.0 550.0 0.02 C
1，0 C
1，1 C
1，2…C
200，4 C
200，5 s
1 s
2…s
165000
Be implemented as follows according to step 4:
(1) from the thermal imagery compression data file, reads all parameters, 165000+1200+4=1651204 altogether.
(2) rebuild the heat wave image sequence according to step 4, the one point data image of reconstruction as shown in Figure 8.
The general effect of example is as follows:
Figure 10 is the 35th frame thermography of original thermal imagery sequence.
Heat wave image for recovering after adopting three kinds of sorting techniques to the respectively process classification of original thermal imagery time series data, reconstruction processing as shown in Figure 11, Figure 13, Figure 15; Be the image after the match shown in Figure 12, Figure 14, Figure 16.The image that recovers after processing by contrast original image and classification and the heat wave image behind the fitting reconfiguration, we can find out, treated image is equally matched with original image Flaw display effect, even better.By the processing of this patent method, according to varying in size of heat wave image, calculated amount and output image memory that thermal imagery is processed significantly reduce, and generally can reduce thousands of times, even upper hundreds of thousands doubly, and compression efficiency improves greatly, and computing velocity significantly improves.
Claims (5)
1. the compression of a heat wave image sequence and reconstructing method is characterized in that: may further comprise the steps:
Step 1: obtain test specimen heat wave image sequence with pulse heat wave method, use heat wave pixel data sequence thermal conductivity law and sequence sorting technique, data sequence is divided into type about 100～200, generate and represent sequence accordingly, and thermal imagery all sequences position is numbered and registered type, generate the classification table;
Step 2: according to one dimension heat wave temperature model and polynomial data fitting algorithm, all are represented the least square fitting that sequence is unified exponent number, obtain the fitting coefficient table of all categories sequence; Unified exponent number is generally got five rank;
Step 3: with thermal imagery acquisition parameter, fitting coefficient table data and the classification table data compressive features as the heat wave image sequence, arrange one by one and generate the one-dimensional data sequence, preserve with binary floating point logarithmic data form, form the heat wave compressed document image, finish compression of images and Computer Storage;
Step 4: use fitting coefficient table and five rank polynomial expression normalized forms, generate the constant duration sequence according to sampling parameter, substitution polynomial expression normalized form rebuilds and reduces that all represents sequence, according to classification table reconstruction heat wave image sequence.
2. the compression of a kind of heat wave image sequence according to claim 1 and reconstructing method is characterized in that: heat wave pixel data sequence thermal conductivity law satisfies shown in formula (1) in the described step 1:
Be the material of h for thickness in the formula, under the effect of heat pulse q, ρ is density of material, c is material specific heat, and T (0, t) be measured surface temperature change with time model, its defectiveness and zero defect place are owing to the reflection of heat wave flow field at fault location, its drop in temperature curve has obvious difference, and along with the propelling of time, its defect information shows as the temperature field at the heat wave image and distributes;
Step 1.1: according to this rule, this method is chosen wherein one section the most obvious continuous 5-10 of defective constantly thermal imagery gray-scale value weighted sum, as its equidistant classification foundation; Or choose wherein one section the most obvious continuous 5-10 of defective moment thermal imagery gray-scale value, utilize the classification of K average Dynamic Clustering Algorithm; Or the gray-scale value of the most obvious certain the frame thermal imagery of selection defective is as equidistant classification foundation.Classification is several to be arranged according to needs, generally selects n=100～200 to get final product;
Step 1.2: after the classification, select the equal value sequence of the center sequence of each class or several center sequences as representing sequence S
i, i=1,2 ..., n, and all pixel sequence locations of thermal imagery are numbered and registered type, classification table S generated.
3. the compression of a kind of heat wave image sequence according to claim 1 and reconstructing method, it is characterized in that: the data fitting method in the described step 2 represents sequence S for all
i, i=1,2 ..., n, and the rule of formula (1) carry out least square fitting, specifically are divided into following a few step:
Step 2.1: eliminate basic infrared emanation.Data sequence about front 18 frames of flash of light is averaged, obtain basal heat radiation m
i, then from representing sequence S
iDeduct basic radiation, obtain new representative sequence
Step 2.2: extract and effectively represent sequence.Find first sequence maximum value position t
m, the position of namely glistening, then take this point as starting point, with thereafter time series data as effectively representing sequence
Reset again data length p=n-t
m+ 1, and rise time Variables Sequence t
i=1,2 ..., p};
Step 2.3: carry out polynomial data fitting.To the time variable sequence with effectively represent sequence and carry out respectively log-transformation, then unified 5 rank polynomial expressions (seeing formula (2)) and the residual error of adopting controlled level, to two least square data fittings that Number Sequence carried out non-equidistance, obtain corresponding fitting coefficient C
i={ c
I0, c
I1..., c
I5;
y
i＝c
i0+c
i1t+c
i2t
2+…+c
i5t
5，i＝1，2，...，n (2)
The compression of a kind of heat wave image sequence according to claim 2 and reconstructing method is characterized in that: thermal imagery acquisition parameter P mainly contains four in the described step 3, is respectively to adopt frame number, employing frame frequency, thermal imagery width and thermal imagery height;
Step 3.1: specific practice is with thermal imagery acquisition parameter P, fitting coefficient table C
iData and classification table S data are arranged its data vector one by one as the compressive features of heat wave image sequence, and namely one by one, separator is not stayed in the centre, generate the one-dimensional data sequence;
Step 3.2: then use binary floating point logarithmic data form, in computing machine, create a user-defined file and preserve, form the heat wave compressed document image, finish compression of images and Computer Storage.
4. the compression of a kind of heat wave image sequence according to claim 3 and reconstructing method is characterized in that: in described step 4, use fitting coefficient table C
iWith polynomial expression normalized form (2), according to time variable sequence t
i=1,2 ..., and the p} logarithmic form rebuilds and reduces that all represents sequence for people's polynomial expression normalized form, and attention will be done exponent arithmetic one time to each data here, reduces original temperature changing regularity; According to the classification table, rebuild the heat wave image sequence with reduction representative sample data sequence at last.
5. the compression of a kind of heat wave image sequence according to claim 4 and reconstructing method, it is characterized in that: the classification number can detect needs according to reality and arrange flexibly, the thermal-image data of a general 1000-2000 frame, its each pixel, be compressed at last in 6 parameters, its longitudinal compression is than being 167-334; The thermal imagery of 640 * 480=307200 or 1024 * 768=786432 point pixel is arranged for every frame, as be compressed into 200 and represent sequence, its horizontal compression ratio can reach 1536 or 3932 so, and overall compression ratio reaches more than 256512 to 1313288 times.
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| CN103728313A (en) * | 2013-12-27 | 2014-04-16 | 华东交通大学 | Infrared nondestructive inspection method based on weighted stacking of time-sequence thermograph |
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| CN109060822A (en) * | 2018-07-17 | 2018-12-21 | 上海大学 | Long pulse Infrared Non-destructive Testing sequence specific primers-polymerase chain reaction method and system |
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| CN110392296A (en) * | 2019-08-07 | 2019-10-29 | 北京航空航天大学 | Aircraft user-defined format is taken a flight test the online playback technology of video image |
| CN110838151A (en) * | 2019-11-12 | 2020-02-25 | 南京甄视智能科技有限公司 | Image compression processing method and device based on polynomial fitting, computer system, server and readable storage medium |
| CN110838151B (en) * | 2019-11-12 | 2020-07-03 | 南京甄视智能科技有限公司 | Picture compression processing method, computer system and readable storage medium |
| CN113506267A (en) * | 2021-07-09 | 2021-10-15 | 中国人民解放军火箭军工程大学 | Metal manufacturing defect repairing method and system |
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