CN109738948B - Spectral data processing method for extracting core oxidation-reduction transition zone information - Google Patents
Spectral data processing method for extracting core oxidation-reduction transition zone information Download PDFInfo
- Publication number
- CN109738948B CN109738948B CN201811560693.4A CN201811560693A CN109738948B CN 109738948 B CN109738948 B CN 109738948B CN 201811560693 A CN201811560693 A CN 201811560693A CN 109738948 B CN109738948 B CN 109738948B
- Authority
- CN
- China
- Prior art keywords
- pixel value
- spectral data
- pixel
- band image
- value
- 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.)
- Active
Links
Landscapes
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention belongs to the technical field of extraction of relevant information of sedimentary uranium deposits, and particularly relates to a spectral data processing method suitable for extracting core redox transition zone information. The invention comprises the following steps: acquiring spectral data of a core sample, and recording spectral measurement positions according to a top-down sequence; numbering the spectral data time lines according to the top-down sequence of the spectrum; preprocessing the spectrum data, and performing atmospheric correction to obtain the reflectivity data of the sample or the ground object spectrum; converting the batch of spectral data into hyperspectral raster image data, wherein each pixel corresponds to one piece of spectral data; step four, resampling the hyperspectral data, and extracting images with wave bands of 423nm, 514nm, 557nm, 612nm, 753nm, 833nm, 887nm and 985 nm; and step five, judging the images in the step four, and determining favorable mineralization zones of the uranium ores. The invention improves the speed of data processing and the accuracy of information extraction, and reduces the influence of human factors.
Description
Technical Field
The invention belongs to the technical field of extraction of relevant information of sedimentary uranium deposits, and particularly relates to a spectral data processing method suitable for extracting core redox transition zone information.
Background
The redox transition zone is an important target for sedimentary uranium ore exploration. The method for extracting the abundance of different types of minerals in the rock through processing spectral data is a common method for mineral spectral analysis at present. The current spectrum processing methods are mainly spectrum full-band matching or spectrum matching of partial continuous bands, specific algorithms include spectrum angles, mixed demodulation filtering and the like, and because the material composition of the earth surface is rarely composed of single minerals, the methods are easily influenced by spectra or noise of other minerals in the information extraction process, and the information extraction precision is low. Secondly, the existing spectral information extraction method has many manual operation steps, and increases the manual judgment error. Therefore, how to reduce the influence of other objects or noise, the influence of manual operation errors and the like in the extraction process of extracting the core oxidation-reduction transition zone information becomes one of the leading edges of the current spectral data processing.
Disclosure of Invention
The technical problems solved by the invention are as follows: the invention provides a spectral data processing method suitable for extracting core oxidation-reduction transition zone information, which simplifies the data processing flow, can process spectral data in batches, extracts target information in a centralized manner, improves the data processing speed and the information extraction precision, and reduces the influence of human factors.
The technical scheme adopted by the invention is as follows:
a spectral data processing method for extracting core oxidation-reduction transition zone information comprises the following steps: acquiring spectral data of a core sample, and recording spectral measurement positions according to a top-down sequence; numbering the spectral data time lines according to the top-down sequence of the spectrum; preprocessing the spectrum data, and performing atmospheric correction to obtain the reflectivity data of the sample or the ground object spectrum; converting the batch of spectral data into hyperspectral raster image data, wherein each pixel corresponds to one piece of spectral data; step four, resampling the hyperspectral data, and extracting images with wave bands of 423nm, 514nm, 557nm, 612nm, 753nm, 833nm, 887nm and 985 nm; and step five, judging the images in the step four, and determining favorable mineralization zones of the uranium ores.
The judgment method in the fifth step is as follows: when the pixel value of the 423nm band image is smaller than the pixel value corresponding to the 514nm band image, judging that the pixel meets the first condition, and obtaining a result image pixel value H1 obtained by subtracting the pixel value of the 423nm band image from the pixel value of the 514nm band image; when the pixel value of the 887nm band image is greater than the pixel value corresponding to the 985nm band image, judging that the pixel meets the second condition, and obtaining a result image pixel value H2 of subtracting the pixel value of the 985nm band image from the pixel value of the 887nm band image; when the pixel value of the 557nm band image is smaller than the pixel value corresponding to the 612nm band image, judging that the pixel meets the third condition, and obtaining a result image pixel value H3 obtained by subtracting the pixel value of the 557nm band image from the pixel value of the 612nm band image; and when the pixel value of the 753nm band image is larger than the pixel value corresponding to the 833nm band image, judging that the pixel meets the condition four.
Selecting pixels which simultaneously meet the conditions of the first and the second to obtain the sum H of the H1 and the H2 in the pixel range; and selecting the pixels which simultaneously satisfy the conditions three and four to obtain H3 in the pixel range.
The value of H represents the abundance value of divalent iron in the pixel, and the larger the value of H, the larger the abundance value of divalent iron in the pixel, namely the content is relatively higher.
The value of H3 represents the abundance value of the trivalent iron in the picture element, and the larger the value of H3, the larger the abundance value of the trivalent iron in the picture element, i.e. the content is relatively higher.
And selecting areas with reduced ferric iron abundance and enhanced ferrous iron abundance as oxidation-reduction transition zones from top to bottom according to the spectral records, wherein the areas are easy to form uranium ores and are favorable ore-forming zones of the uranium ores.
The extraction bands are 423 + -5 nm, 514 + -5 nm, 557 + -5 nm, 612 + -5 nm, 753 + -5 nm, 833 + -5 nm, 887 + -5 nm and 985 + -5 nm.
The invention has the beneficial effects that:
the oxidation-reduction transition zone plays an important role in uranium ore exploration, and most sedimentary uranium deposits in the oxidation-reduction transition zone are located in the world. The method can be used for extracting the spectral data of the core data, and has the advantages of easy programming, rapid and accurate extraction of the position of the redox transition zone in the core, important effect on uranium ore exploration, improvement of the efficiency and precision of the uranium ore exploration and remarkable economic benefit due to the adoption of spectral conversion into grids and accurate wave band positioning.
Detailed Description
The invention provides a spectral data processing method suitable for extracting core oxidation-reduction transition zone information, which comprises the following specific steps:
acquiring spectral data of a core sample, and recording spectral measurement positions according to a top-down sequence; the spectral data are time-line numbered in the top-down order of the spectrum.
And secondly, preprocessing the spectrum data, performing atmospheric correction, and acquiring the reflectivity data of the sample or the ground object spectrum.
And step three, converting the batch of spectral data into hyperspectral raster image data, wherein each pixel corresponds to one piece of spectral data.
And step four, resampling the hyperspectral data, and extracting images with wave bands of 423nm, 514nm, 557nm, 612nm, 753nm, 833nm, 887nm and 985 nm.
And step five, when the pixel value of the 423nm wave band image is smaller than the corresponding pixel value of the 514nm wave band image, judging that the pixel meets the first condition, and obtaining a result image pixel value H1 of subtracting the pixel value of the 423nm wave band image from the pixel value of the 514nm wave band image.
And step six, when the pixel value of the 887nm band image is greater than the pixel value corresponding to the 985nm band image, judging that the pixel meets the second condition, and obtaining a result image pixel value H2 of subtracting the pixel value of the 985nm band image from the pixel value of the 887nm band image.
And seventhly, when the pixel value of the 557nm band image is smaller than the pixel value corresponding to the 612nm band image, judging that the pixel meets the third condition, and obtaining a result image pixel value H3 of subtracting the pixel value of the 557nm band image from the pixel value of the 612nm band image.
And step eight, when the pixel value of the 753nm band image is larger than the pixel value corresponding to the 833nm band image, judging that the pixel meets the condition four.
And step nine, selecting the pixels meeting the conditions of the first and the second simultaneously, and obtaining the sum H of the H1 and the H2 in the pixel range. The value of H represents the abundance value of divalent iron in the pixel, and the larger the value of H, the larger the abundance value of divalent iron in the pixel, namely the content is relatively higher. And selecting the pixels which simultaneously satisfy the conditions three and four to obtain H3 in the pixel range. The value of H3 represents the abundance value of the trivalent iron in the picture element, and the larger the value of H3, the larger the abundance value of the trivalent iron in the picture element, i.e. the content is relatively higher.
And step ten, selecting areas with reduced trivalent iron abundance and enhanced divalent iron abundance as redox transition zones according to the sequence of the spectral records from top to bottom, wherein the areas are easy to form uranium ores and are favorable ore-forming zones of the uranium ores.
The error of the band selection position in the above steps is only within 5nm in the control. The abundance information is volume relative content information in a mixture of single substances, and the higher the abundance, the higher the volume content of the single substances in the mixture.
Claims (7)
1. A spectral data processing method for extracting core oxidation-reduction transition zone information is characterized by comprising the following steps: the method comprises the following steps:
acquiring spectral data of a core sample, and recording spectral measurement positions according to a top-down sequence; numbering the spectral data time lines according to the top-down sequence of the spectrum;
preprocessing the spectrum data, and performing atmospheric correction to obtain the reflectivity data of the sample or the ground object spectrum;
converting the batch of spectral data into hyperspectral raster image data, wherein each pixel corresponds to one piece of spectral data;
step four, resampling the hyperspectral data, and extracting images with wave bands of 423nm, 514nm, 557nm, 612nm, 753nm, 833nm, 887nm and 985 nm;
and step five, judging the images in the step four, and determining favorable mineralization zones of the uranium ores.
2. The spectral data processing method for extracting core redox transition zone information according to claim 1, characterized in that: the judgment method in the fifth step is as follows: when the pixel value of the 423nm band image is smaller than the pixel value corresponding to the 514nm band image, judging that the pixel meets the first condition, and obtaining a result image pixel value H1 obtained by subtracting the pixel value of the 423nm band image from the pixel value of the 514nm band image; when the pixel value of the 887nm band image is greater than the pixel value corresponding to the 985nm band image, judging that the pixel meets the second condition, and obtaining a result image pixel value H2 of subtracting the pixel value of the 985nm band image from the pixel value of the 887nm band image; when the pixel value of the 557nm band image is smaller than the pixel value corresponding to the 612nm band image, judging that the pixel meets the third condition, and obtaining a result image pixel value H3 obtained by subtracting the pixel value of the 557nm band image from the pixel value of the 612nm band image; and when the pixel value of the 753nm band image is larger than the pixel value corresponding to the 833nm band image, judging that the pixel meets the condition four.
3. The spectral data processing method for extracting core redox transition zone information according to claim 2, characterized in that: selecting pixels which simultaneously meet the conditions of the first and the second to obtain the sum H of the H1 and the H2 in the pixel range; and selecting the pixels which simultaneously satisfy the conditions three and four to obtain H3 in the pixel range.
4. The spectral data processing method for extracting core redox transition zone information according to claim 3, characterized in that: the value of H represents the abundance value of divalent iron in the pixel, and the larger the value of H, the larger the abundance value of divalent iron in the pixel, namely the content is relatively higher.
5. The spectral data processing method for extracting core redox transition zone information according to claim 3, characterized in that: the value of H3 represents the abundance value of the trivalent iron in the picture element, and the larger the value of H3, the larger the abundance value of the trivalent iron in the picture element, i.e. the content is relatively higher.
6. A spectral data processing method for extracting core redox transition zone information according to claim 4 or 5, characterized by: and selecting areas with reduced ferric iron abundance and enhanced ferrous iron abundance as oxidation-reduction transition zones from top to bottom according to the spectral records, wherein the areas are easy to form uranium ores and are favorable ore-forming zones of the uranium ores.
7. The spectral data processing method for extracting core redox transition zone information according to claim 2, characterized in that: the extraction bands are 423 + -5 nm, 514 + -5 nm, 557 + -5 nm, 612 + -5 nm, 753 + -5 nm, 833 + -5 nm, 887 + -5 nm and 985 + -5 nm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811560693.4A CN109738948B (en) | 2018-12-20 | 2018-12-20 | Spectral data processing method for extracting core oxidation-reduction transition zone information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811560693.4A CN109738948B (en) | 2018-12-20 | 2018-12-20 | Spectral data processing method for extracting core oxidation-reduction transition zone information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109738948A CN109738948A (en) | 2019-05-10 |
| CN109738948B true CN109738948B (en) | 2020-10-23 |
Family
ID=66360682
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811560693.4A Active CN109738948B (en) | 2018-12-20 | 2018-12-20 | Spectral data processing method for extracting core oxidation-reduction transition zone information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109738948B (en) |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6307629B1 (en) * | 1997-08-12 | 2001-10-23 | Lj Laboratories, L.L.C. | Apparatus and method for measuring optical characteristics of an object |
| CN102609711B (en) * | 2012-02-21 | 2013-08-28 | 核工业北京地质研究院 | Information extraction method applicable to hyperspectral image |
| CN107991243B (en) * | 2016-10-27 | 2020-06-19 | 核工业北京地质研究院 | High-altitude area water body extraction method based on aviation hyperspectral remote sensing data |
| CN106570912B (en) * | 2016-10-28 | 2019-08-13 | 核工业北京地质研究院 | A method of imaging EO-1 hyperion drill core data alteration is extracted |
| CN108956483A (en) * | 2017-05-27 | 2018-12-07 | 核工业北京地质研究院 | A kind of quick technique for delineating of Airborne Hyperspectral remote sensing in volcanic type uranium mineralization location |
| CN108171210B (en) * | 2018-01-18 | 2020-06-19 | 中国地质科学院矿产资源研究所 | Method and system for extracting remote sensing abnormal information of alteration of covered area of planting |
-
2018
- 2018-12-20 CN CN201811560693.4A patent/CN109738948B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN109738948A (en) | 2019-05-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yang et al. | Urban surface water body detection with suppressed built-up noise based on water indices from Sentinel-2 MSI imagery | |
| AU2020101520A4 (en) | Method for identifying exposed and buried fault structures in granite-type uranium province | |
| CN102663337B (en) | Method for quick Data Matrix two-dimensional barcode identifying under simple condition background | |
| CN101950359B (en) | Method for recognizing rock type | |
| CN105046188A (en) | MODIS mixed pixels decomposition forest information extraction method | |
| CN108171210B (en) | Method and system for extracting remote sensing abnormal information of alteration of covered area of planting | |
| CN110472636A (en) | Water gauge E font scale recognition methods based on deep learning | |
| CN106570912B (en) | A method of imaging EO-1 hyperion drill core data alteration is extracted | |
| CN111678882B (en) | Method for predicting weathering crust ion adsorption type rare earth deposit horizon through ancient diving space | |
| Struve et al. | Neodymium isotopes and concentrations in aragonitic scleractinian cold-water coral skeletons-Modern calibration and evaluation of palaeo-applications | |
| CN105787950A (en) | Infrared image sea-sky-line detection algorithm based on line gradient accumulation | |
| CN105787915A (en) | Hyperspectral image processing method for extracting information of jarosite | |
| CN109738948B (en) | Spectral data processing method for extracting core oxidation-reduction transition zone information | |
| CN113625363A (en) | Mineral exploration method and device for pegmatite-type lithium ore, computer equipment and medium | |
| Li | Textural and rule-based lithological classification of remote sensing data, and geological mapping in Southwestern Prieska sub-basin, Transvaal Supergroup, South Africa | |
| CN103901497B (en) | A kind of Technique for Hyper-spectral Images Classification for illite information extraction | |
| CN106198402A (en) | A kind of basic rock recognition methods based on space flight Multi-spectral Remote Sensing Data | |
| CN113837123A (en) | Mid-resolution remote sensing image offshore culture area extraction method based on spectral-spatial information combination | |
| CN109785318B (en) | Remote sensing image change detection method based on facial line primitive association constraint | |
| CN109738369B (en) | Archaeological detection method adopting aviation hyperspectral remote sensing jade | |
| CN111159323A (en) | Method for identifying sandstone-type uranium ore path-filling and discharging system based on multi-source geoscience information | |
| CN109839356A (en) | Alteration information extraction method based on WorldView-3 satellite data | |
| CN114386498A (en) | Method for extracting iron dyeing information by using WorldView-3 remote sensing data | |
| CN112464834B (en) | Multisource remote sensing identification method for different-period secondary rock mass in white sentry uranium mining area | |
| CN109657637B (en) | Method for distinguishing hematite in different rocks by using CASI image |
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 |