CN103902998A - High-spectral image processing method for chlorite information extraction - Google Patents
High-spectral image processing method for chlorite information extraction Download PDFInfo
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- CN103902998A CN103902998A CN201210580124.2A CN201210580124A CN103902998A CN 103902998 A CN103902998 A CN 103902998A CN 201210580124 A CN201210580124 A CN 201210580124A CN 103902998 A CN103902998 A CN 103902998A
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Abstract
The invention belongs to an information extraction method, and specifically relates to a high-spectral image processing method for chlorite information extraction. The method comprises: step one, wave band sampling; step two, determining; and step three, calculating, i.e., performing calculating by use of a determination result obtained from step two, and obtaining abundance. The advantages are as follows: resampling is carried out on a high-spectral image, a specific wave band is extracted, and a series of determining and calculating are carried out, so that the abundance values of kaolin in different areas in an image scope can be accurately calculated.
Description
Technical field
The invention belongs to information extracting method, be specifically related to a kind of Technique for Hyper-spectral Images Classification for chlorite information extraction.
Background technology
By Image Information Processing being extracted to the abundance of dissimilar mineral in image-region, it is the conventional method of current Exploration Domain.This method does not need staff directly to arrive ground observation, sampling, can extract the abundance of dissimilar mineral.The chlorite information extracting method of current target in hyperspectral remotely sensed image is mainly spectrum all band coupling or the Spectral matching of partial continuous wave band, specific algorithm has spectrum angle, mixes demodulation filtering etc., because the material on earth's surface forms seldom by single mineral composition, these methods are subject to the impact of other ground-object spectrums or noise in the process of information extraction, information extraction precision is relatively low.Secondly existing spectrum extracting method manual steps is many, has increased artificial error in judgement.The 3rd is that high-spectral data wave band is many, and data volume is large, and the existing method processing time is long, has reduced speed and the application scale of data processing.Therefore, how in the process of chlorite information extraction, to reduce impact, manual steps and the deal with data amount of other atural objects or noise, become one of forward position of current target in hyperspectral remotely sensed image processing.
Summary of the invention
The present invention is directed to the defect of prior art, a kind of Technique for Hyper-spectral Images Classification for chlorite information extraction is provided.
The present invention is achieved in that a kind of Technique for Hyper-spectral Images Classification for chlorite information extraction, comprises,
Step 1: wave band sampling
Airborne-remote sensing to existing ground surface reflectance is sampled, extract wave band at 1130nm, 1790nm, 2165nm, 2255nm, 2270nm, 2330nm, the image of 2360nm, and be recorded as successively b1～b7, what each sampling obtained is all a width gray-scale map, and in figure, the value of each pixel is its gray-scale value
Step 2: judgement
By carrying out a series of judgements below, and record result
A1=(b1 is less than b2);
A2=(b3 is greater than b4);
A3=(b5 is greater than b6);
A4=(b6 is less than b7);
Above-mentioned judgement is to judge for the corresponding pixel of each judgement image, and in the time that judged result is "Yes", recording judged result is 1, is 0 otherwise record result,
Step 3: calculate
Calculate b8 with following formula
b8=b2+b3+b5+b7-b1-b4-2*b6
Described * represents to multiply each other,
With the a0 of formula calculating below
a0=a1*a2*a3*a4*b8
Above-mentioned all calculating is corresponding pixel and calculates, and uses the corresponding pixel of different images to calculate.
Effect of the present invention is: the present invention extracts specific band, carries out a series of judgements and calculating, can calculate accurately the Abundances of the zones of different chlorite in image capturing range.Retain the obvious wave band of spectral signature of chlorite, remove the unconspicuous wave band of other features, thereby give prominence to the spectral signature of chlorite in the process of information extraction, reduce the impact of other atural objects or noise, reduce the data volume of processing, and can reach the object that realizes net result information extraction with less manual operation by IDL program, improve precision and the speed of chlorite information extraction.
Embodiment
Below in conjunction with embodiment, the invention will be further described.For a Technique for Hyper-spectral Images Classification for chlorite information extraction, comprise,
Step 1: wave band sampling
Airborne-remote sensing to existing ground surface reflectance is sampled, extract wave band at 1130nm, 1790nm, 2165nm, 2255nm, 2270nm, 2330nm, the image of 2360nm, and be recorded as successively b1～b7, be that b1 is the sampled data of wave band 1130nm, b2 is the sampled data of wave band 1790nm, by that analogy.What each sampling obtained is all a width gray-scale map, and in figure, the value of each pixel is its gray-scale value, and b1 is a width gray-scale map, and the value of (1,1) point of b1 image is gray-scale value, the rest may be inferred for all the other points, and all the other sample graph also.
Step 2: judgement
By carrying out a series of judgements below, and record result
A1=(b1 is less than b2);
A2=(b3 is greater than b4);
A3=(b5 is greater than b6);
A4=(b6 is less than b7);
Above-mentioned judgement is to judge for the corresponding pixel of each judgement image, be less than b2 take a1=(b1) be example, get the gray-scale value of certain pixel (for example (1,1) point) of b1 image, with the corresponding pixel of b2 image (when b1 image is got (1,1) point, b2 image also must be got (1,1) point) gray-scale value, then according to judgment rule " b1 is less than b2 " judgement, in the time that judged result is "Yes", recording judged result is 1, is 0 otherwise record result.Therefore when a1=(b1 is less than b2) judge that when complete, the a1 obtaining is and the matrix of b1 matrix formed objects that wherein the value of each point is the judged result (value that is each point is 0 or 1) obtaining according to judgment rule.
Other judgement is also carried out according to similar rule.After finishing, this step obtains a1～a4, totally 4 matrixes (image).
Step 3: calculate
Calculate b8 with following formula
b8=b2+b3+b5+b7-b1-b4-2*b6
Described * represents to multiply each other.
With the a0 of formula calculating below
a0=a1*a2*a3*a4*b8
Above-mentioned all calculating is corresponding pixel and calculates, and uses the corresponding pixel of different images to calculate.Take b8=b2+b3+b5+b7-b1-b4-2*b6 formula as example, when calculation level (x, y), the gray-scale value of getting the point (x, y) of b2, b3, b5, b7, b1, b4, b6 participates in calculating, and the result obtaining is the value of the point (x, y) of b8.For example a0=a1*a2*a3*a4*b8 again, when calculation level (x, y), the value of getting the point (x, y) of a1, a2, a3, a4, b10 participates in calculating, and the result obtaining is the value of the point (x, y) of a0.
The a0 calculating is exactly the abundance figure of chlorite information, and in image, the abundance of this region chlorite of the larger expression of the numerical value in certain region is higher.
Patent meaning: this patent can reduce the data volume of processing, the wave band quantity of SASI is 101 wave bands, this method is only for 7 wave bands, data volume has reduced 93%, and owing to being computing machine from moving a step extraction, reduced the operation stepss such as the selection of principal component transform, end member wave spectrum, arithmetic speed can improve more than 14 times.Owing to having removed most of wave band little to information extraction relation, reduce the interference to its spectrum of other materials or noise, improve the precision of information extraction.Rapid extraction to chlorite information in airborne-remote sensing has good function and significance.
The wave spectrum position of each wave band sampling of step 1 is to set according to each wave band position of SASI sensor, each band selection of other different sensors should be adjusted according to actual conditions, substantially in more than in the scope of (SASI) the wave band position ± 5nm.
Claims (1)
1. for a Technique for Hyper-spectral Images Classification for chlorite information extraction, comprise,
Step 1: wave band sampling
Airborne-remote sensing to existing ground surface reflectance is sampled, extract wave band at 1130nm, 1790nm, 2165nm, 2255nm, 2270nm, 2330nm, the image of 2360nm, and be recorded as successively b1～b7, what each sampling obtained is all a width gray-scale map, and in figure, the value of each pixel is its gray-scale value
Step 2: judgement
By carrying out a series of judgements below, and record result
A1=(b1 is less than b2);
A2=(b3 is greater than b4);
A3=(b5 is greater than b6);
A4=(b6 is less than b7);
Above-mentioned judgement is to judge for the corresponding pixel of each judgement image, and in the time that judged result is "Yes", recording judged result is 1, is 0 otherwise record result,
Step 3: calculate
Calculate b8 with following formula
b8=b2+b3+b5+b7-b1-b4-2*b6
Described * represents to multiply each other,
With the a0 of formula calculating below
a0=a1*a2*a3*a4*b8
Above-mentioned all calculating is corresponding pixel and calculates, and uses the corresponding pixel of different images to calculate.
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