A method for fusing and matching gamma radiation images and two-dimensional laser radar scanning information

Abstract

The present application relates to the technical field of image processing, in particular to a method for fusing and matching gamma radiation image and two-dimensional laser radar scanning information. The method comprises the following steps: collecting gamma radiation image and two-dimensional laser radar scanning point cloud image of a target object respectively; pre-processing the gamma radiation image and two-dimensional laser radar scanning point cloud image; selecting a radiation hotspot feature region from the pre-processed gamma radiation image based on a hotspot peak value; mapping elements of the radiation hotspot feature region to a polar coordinate system, calculating an azimuth angle parameter thereof, and registering the azimuth angle parameter with a point cloud pixel of a radar feature region; attaching a pseudo-color map of the registered gamma radiation image to the corresponding radar point cloud pixel to generate a fusion image. The present application can fuse the pixel azimuth angle feature of the radiation image and the characteristics of the radar scanning point cloud information elements, thereby improving the visualization effect and imaging quality of the radiation image.

Description

A method for fusing and matching gamma radiation images and two-dimensional lidar scanning information Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method for fusing and matching gamma radiation images and two-dimensional lidar scanning information. Background Technology

[0002] In the field of gamma-ray detection and imaging of radioactive materials, gamma-ray radiation imaging technology can intuitively indicate the spatial distribution of radioactive materials through hotspot imaging, and has broad application prospects in nuclear radiation monitoring, nuclear facility decommissioning, and nuclear emergency response. Taking coded aperture imaging technology as an example, it has become one of the mainstream radiation imaging technologies, with advantages such as high angular resolution and high imaging sensitivity. However, radiation images lack distance information of radiation hotspots, making it impossible to determine the attachment points of radioactive materials and their true distribution. In contrast, radar scan point cloud images can provide information on the location, shape, and size of objects. Therefore, a method for fusing these two types of image information is needed to improve the accuracy and reliability of radiation imaging. To this end, this invention proposes a method for fusing and matching gamma-ray radiation images and two-dimensional lidar scanning information. Summary of the Invention

[0003] To address at least one of the aforementioned technical problems, this invention proposes a method for fusing and matching gamma radiation images and two-dimensional lidar scanning information.

[0004] This invention is achieved through the following technical solution: a method for fusing and matching gamma radiation images and two-dimensional lidar scanning information, comprising the following steps:

[0005] Step 1: Acquire gamma radiation images and two-dimensional lidar scan point cloud images of the target object, respectively;

[0006] Step 2: Preprocess the gamma radiation image and the two-dimensional lidar scan point cloud image;

[0007] Step 3: Select radiation hotspot feature regions from the preprocessed gamma radiation image based on the hotspot peak value; and extract radar feature regions corresponding to the azimuth angle of the radiation hotspot feature regions from the preprocessed two-dimensional lidar scan point cloud image.

[0008] Step 4: Map the elements of the radiation hotspot feature region to the polar coordinate system, calculate its azimuth parameters, and register them with the point cloud pixels of the radar feature region;

[0009] Step 5: Attach the registered gamma radiation image pseudo-color map to the corresponding radar point cloud pixels to generate a fused image.

[0010] Preferably, in step one, the gamma radiation image is acquired by an coded aperture gamma camera with an imaging field of view of 40°×40° and an angular resolution of 2°; the field of view of the two-dimensional lidar scanning point cloud image is 60°×120° and an angular resolution of 1°.

[0011] Preferably, in step two, the preprocessing includes noise removal and contrast enhancement. The noise removal method for the gamma radiation image is: using 50% of the peak value of the hotspot as a threshold, artifact noise below this threshold is shielded. The noise removal method for the two-dimensional lidar scan point cloud image is: based on local neighborhood statistics, outliers that deviate from the average value by more than 2 standard deviations are removed.

[0012] Preferably, in step four, the formula for calculating the azimuth parameters (phi, theta) is:

[0013] ;

[0014] ;

[0015] Where (peak_X, peak_Y) are the coordinates of the peak value of the radiation hotspot, (X, Y) are the coordinates of the elements in the feature region of the radiation hotspot, and S is the distance value corresponding to the radar point cloud pixel.

[0016] Preferably, in step four, the registration operation specifically involves: indexing continuous regions with the same azimuth angle in the radar point cloud image based on the polar coordinate azimuth angle of the elements in the radiation hotspot feature region, and establishing a one-to-one mapping relationship between radiation image elements and radar point cloud pixels.

[0017] Preferably, in step four, the pseudo-color map is color-coded according to the radiation intensity value, and the color information is superimposed on the corresponding radar point cloud pixels to form a fused image with a three-dimensional spatial distribution.

[0018] Preferably, in step three, the radiation hotspot feature region is a closed region centered on the hotspot peak and whose adjacent elements are non-zero values.

[0019] Preferably, in step three, the extraction of the radar feature region includes: based on the azimuth continuity judgment, extracting a continuous point cloud region that matches the azimuth of the radiation hotspot feature region.

[0020] Preferably, in step five, the radiation intensity color attribute and the spatial position attribute of the radar point cloud in the generated fused image are displayed synchronously through a three-dimensional coordinate system.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] 1. Traditional radiation images can only represent azimuth information, and the angle range corresponding to each pixel is different. They cannot give the specific distribution location of radioactive materials indicated by radiation hotspots. By fusing with radar point cloud information, the spatial distribution location of radioactive materials can be accurately given.

[0023] 2. The radar scan image mentioned in this invention is a large-field-of-view point cloud information. Traditional laser ranging can only provide the distance to a single point, while the radiation image and radar image fusion method proposed in this invention targets large-field-of-view multi-pixel messenger matching. By matching azimuth information in polar coordinates, the two-dimensional radiation image is fused with the three-dimensional radar point cloud image to achieve the effect of three-dimensional radiation imaging. This invention provides a multi-messenger fusion method for radiation images, which, combined with radar large-field-of-view three-dimensional point cloud information, can achieve accurate three-dimensional radiation imaging and radioactive material positioning. This invention provides a supplement and methodological innovation to the field of nuclear radiation detection imaging, improves the imaging quality and positioning accuracy of radiation sources, and has broad application prospects in nuclear radiation monitoring, nuclear facility decommissioning, nuclear emergency response, and nuclear security. Attached Figure Description

[0024] Figure 1 is a flowchart of the present invention.

[0025] Figure 2 shows the radiation map of the observed target acquired by the gamma camera.

[0026] Figure 3 shows the point cloud map collected by the radar.

[0027] Figure 4 shows the denoising result of the radiometric image in Figure 2.

[0028] Figure 5 shows the denoising result of the radar image in Figure 3.

[0029] Figure 6 shows the radiation thermal characteristic region of the radiation image in Figure 4.

[0030] Figure 7 shows the radar feature region map of the radar image in Figure 5.

[0031] Figure 8 is an elemental diagram of the radiation hotspot image in Figure 6.

[0032] Figure 9 is a fusion of gamma radiation image and two-dimensional radar scan image. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "or / and" as used herein includes any and all combinations of one or more of the associated listed items.

[0035] Please refer to Figures 1-9. This embodiment provides the steps of the present invention as shown in Figure 1, including:

[0036] The radiation image of the observed target is acquired by a gamma camera. Taking a typical coded gamma camera as an example, the imaging field of view is about 40°×40° and the angular resolution is 2°. The image is numerically represented as a 20×20 two-dimensional array, as shown in Figure 2.

[0037] The scene is observed by using a lidar with a large field of view, which is larger than that of the radiation image, for example, 60°×120°. The angular resolution is also better than that of the radiation image, for example, 1°. The point cloud image collected by the lidar is shown in Figure 3.

[0038] Noise reduction was performed on both the radiometric and radar images. In the radiometric image, artifact noise was masked by using 50% of the peak value of the hotspot. For the original radar point cloud image, statistical methods were used to identify and remove abnormal noise values. Specifically, the mean and standard deviation within the local neighborhood of each point were calculated, and points far from the mean were removed. The criterion for identifying noise points was two standard deviations. The denoising results are shown in Figures 4 and 5.

[0039] Feature points were extracted from the radiometric image and the radar image. For the radiometric image, hotspot peaks were selected as the baseline, and the regions whose adjacent elements were not zero were selected as the feature regions. For the radar image, the continuous regions at the azimuth angle corresponding to the hotspot peaks in the radiometric image were selected as the feature regions. The feature regions for both are shown in Figures 6 and 7.

[0040] The elements corresponding to the radiation hotspots in the gamma radiation image are mapped to azimuth angles in a polar coordinate system, and the corresponding radar point cloud pixels are selected based on the polar coordinate values ​​of the elements in the feature region of the radiation hotspot. The radiation image elements processed are shown in Figure 8.

[0041] Where the coordinates of the peak of the radiating hotspot are (peak_X, peak_Y), the coordinates of each element in the hotspot feature region are (X, Y), and the distance of the radar point cloud pixel corresponding to the azimuth angle of the hotspot peak is S, then the formulas for calculating the polar coordinate azimuth angles phi and theta of the elements in the radiating hotspot feature region are:

[0042] ;

[0043] ;

[0044] Each element in the radiation hotspot feature region points to a specific radar point cloud pixel according to its azimuth angle (phi, theta). Then, a pseudo-color texture of the radiation image is attached to the corresponding pixel of the radar point cloud information to achieve registration. The registered gamma radiation image and the two-dimensional radar scan image are then fused into a single image, as shown in Figure 9.

[0045] This invention proposes a dual-optical-path matching method for gamma radiation images and radar scanning information, providing a new technical means for radiation imaging methods. This invention can fuse the pixel azimuth features of the radiation image and the characteristics of the radar scanning point cloud information elements to accurately give the specific spatial location of the distribution of radioactive materials or the attachment point of objects, thereby improving the visualization effect and imaging quality of radiation images.

[0046] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for fusing and matching gamma radiation images and two-dimensional lidar scanning information, characterized in that, Includes the following steps: Step 1: Acquire gamma radiation images and two-dimensional lidar scan point cloud images of the target object respectively; Step 2: Preprocess the gamma radiation images and two-dimensional lidar scan point cloud images. Step 3: Select radiation hotspot feature regions from the preprocessed gamma radiation image based on the hotspot peak value; And extract the radar feature region corresponding to the azimuth angle of the radiation hotspot feature region from the preprocessed two-dimensional lidar scan point cloud image; Step Step 4: Map the elements of the radiation hotspot feature region to the polar coordinate system, calculate its azimuth parameters, and register them with the point cloud pixels of the radar feature region; Step 5: Attach the registered gamma radiation image pseudo-color texture to the corresponding radar point cloud pixels to generate a fused image.

2. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step one, the gamma radiation image is acquired by an coded aperture gamma camera with an imaging field of view of 40°×40° and an angular resolution of 2°; the field of view of the two-dimensional lidar scanning point cloud image is 60°×120° and an angular resolution of 1°.

3. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step two, the preprocessing includes noise removal and contrast enhancement. The noise removal method for the gamma radiation image is to use 50% of the peak value of the hotspot as a threshold to block artifact noise below the threshold. The noise removal method for the two-dimensional lidar scan point cloud image is to remove outliers that deviate from the average value by more than 2 standard deviations based on local neighborhood statistics.

4. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step four, the formula for calculating the azimuth parameters (phi, theta) is as follows: ； Where (peak_X, peak_Y) are the coordinates of the peak value of the radiation hotspot, (X, Y) are the coordinates of the elements in the feature region of the radiation hotspot, and S is the distance value corresponding to the radar point cloud pixel.

5. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step four, the registration specifically involves: based on the polar coordinate azimuth of the elements in the radiation hotspot feature region, indexing continuous regions at the same azimuth in the radar point cloud image, and establishing a one-to-one mapping relationship between radiation image elements and radar point cloud pixels.

6. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step four, the pseudo-color map is color-coded according to the radiation intensity value, and the color information is superimposed on the corresponding radar point cloud pixels to form a fused image with a three-dimensional spatial distribution.

7. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step three, the radiation hotspot characteristic region is a closed region centered on the hotspot peak and whose adjacent elements are non-zero values.

8. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step three, the extraction of the radar feature region includes: based on the azimuth continuity judgment, extracting a continuous point cloud region that matches the azimuth of the radiation hotspot feature region.

9. The method for fusing and matching gamma radiation images and two-dimensional lidar scanning information according to claim 1, characterized in that, In step five, the radiation intensity color attribute and the spatial location attribute of the radar point cloud are synchronously displayed in the generated fused image through a three-dimensional coordinate system.

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