Image processing method based on infrared area array search system

Abstract

The invention provides an image processing method based on an infrared area array search system, which solves the problems of panorama splicing error, target azimuth angle calculation error, target repeated alarm and the like caused by azimuth field angle distortion of each frame of image when the pitch angle of equipment is increased. According to the method, two sides of each frame of image are cut in real time by analyzing a change relationship between a pitch angle and an azimuth field angle of an infrared area array search system, so that the number of pixels in an image overlapping region is ensured to be unchanged. A foundation is laid for subsequent image splicing, target detection and target azimuth angle settlement, and the correctness of target identification is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of image processing, and in particular relates to an image processing method based on an infrared surface array search system. Background Art

[0002] The infrared array search system achieves a 360° wide field of view monitoring range through high frame rate real-time imaging, and can monitor targets in low and high altitudes by adjusting the pitch. The infrared array search system needs to output each frame of image clearly, including the corresponding azimuth pitch angle information, to facilitate subsequent splicing, target detection and recognition and other processing.

[0003] When designing an infrared array detector, the device parameters are often collected when the device pitch is at 0° or low pitch, and the azimuth field of view of each frame of the image collected by the device is experimentally calculated. Subsequent image stitching, target detection, etc. are all image processing based on this angle. However, due to the characteristics of detector imaging, the azimuth field of view changes in real time according to the pitch angle. The larger the pitch angle, the more obvious the azimuth field of view distortion. As shown in Formula 3, the overlapping area of ​​the previous and next frames gradually increases.

[0004] Existing algorithms use fixed-width overlapping areas for real-time panorama stitching and real-time target detection. However, when the device is at a high pitch angle, the overlapping area becomes larger, and there are a large number of repeated areas in the two frames of images. Image processing based on the fixed-width overlapping area method will cause panorama stitching errors, resulting in repeated target alarms, etc. In addition, since the target angle is calculated based on the field of view angle, the target azimuth is calculated incorrectly.

[0005] In summary, an algorithm is needed to calculate the azimuth field of view angle in real time according to the change of the pitch angle to solve the problem of azimuth field of view distortion caused by high elevation angles. Summary of the invention

[0006] In order to solve the problems of azimuth field distortion caused by high elevation angle, resulting in larger azimuth field angle, image splicing errors, repeated target detection, target azimuth angle calculation errors, etc. In order to ensure that the original image splicing, target recognition, and coordinate conversion algorithms are changed to the minimum, the present invention proposes an image processing method based on an infrared array search system, which calculates the field size in real time according to the pitch angle of the device, and then calculates the pixel width of the cropped area based on the effective field angle size and the horizontal overlapping area retained in each frame of the image.

[0007] As the pitch angle of the device increases, the azimuth angle covered by each pixel of the two frames of images collected by the device increases, but the effective field of view angle of each frame remains unchanged.

[0008] The method comprises the following steps:

[0009] 1. The infrared array search system collects N frames of images in one circle, and the field of view at the center of each frame is taken as the effective field of view angle fov e .

[0010]

[0011] 2. A single frame image has X pixels in the horizontal direction, and its azimuth field of view is fov x , calculate the number of overlapping pixels per frame image as D x :

[0012]

[0013] 3. When the device is horizontal, the pitch angle baseline value is The azimuth field of view size at this time is the field of view size set by the device, recorded as: The number of overlapping pixels is calculated by the above formula when the device is horizontal.

[0014] 4. Read the current pitch angle baseline value: θ y , calculate the current azimuth field of view fov x :

[0015]

[0016] 5. The number of overlapping pixels when each frame image is kept horizontally is Crop both sides of each frame to ensure that the number of pixels in the overlapping area of ​​the image remains unchanged. The number of pixels C that need to be cropped on both sides of each frame is calculated by the following formula: x :

[0017]

[0018] 6. The number of cropped pixels C obtained by calculation x The pixel left boundary C retained horizontally for each image can be calculated Left , right boundary C Right .

[0019] C Left =C x (11)

[0020] C Right =XC x (12)

[0021] 7. According to the calculated left boundary C Left , right boundary C Right , crop each frame of the image, and calculate the cropping area in real time so that the number of overlapping pixels of each frame of the image remains unchanged, which is Then the retained images are subjected to subsequent processing such as image stitching and target detection.

[0022] The beneficial effects of the present invention are that the algorithm has low computational complexity, saves computing time, consumes less resources, can well meet real-time requirements, and has small algorithm changes. By calculating the cropping width in real time, the number of pixels in the overlapping area between each frame of the image is guaranteed and will not change with the pitch angle of the infrared search device, thus laying a good foundation for subsequent image stitching, target detection and tracking, and target coordinate calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0024] Figure 1 For flow chart

[0025] Figure 2 Schematic diagram of overlapping area changing with pitch angle

[0026] Figure 3 Schematic diagram of overlapping area cutting of the present invention DETAILED DESCRIPTION

[0027] The technical scheme in the embodiment of the present invention will be described in detail below in conjunction with the accompanying drawings in the embodiment of the present invention. Several parameters are involved, and these parameters need to be adjusted according to the specific processing environment to achieve good performance. Based on the embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0028] Scope of application: Infrared images collected by infrared surface array scanning system.

[0029] Application environment: Code Composer Studio V6.0

[0030] Image: The images used in the experiment are 16-bit grayscale images.

[0031] Test steps:

[0032] 1) The infrared array search system used in the laboratory will collect 120 frames of images in one rotation. The center azimuth angle of each frame is taken as the effective field angle:

[0033]

[0034] 2) A single frame image has 1024 pixels in the horizontal direction. When the device is horizontal, the pitch angle baseline value is The azimuth field of view size at this time is the field of view size set by the device, recorded as: 3.6°. The number of overlapping pixels is calculated by the above formula to obtain the number of overlapping pixels when the device is horizontal:

[0035]

[0036] In order to prevent the target from being lost,

[0037] 3) If the pitch baseline value θ at this time y =30°, the current azimuth field of view is:

[0038]

[0039] 4) The number of pixels that need to be cropped on both sides of each frame of the image is calculated using the following formula:

[0040]

[0041] 5) The number of cropped pixels C obtained by calculation x The pixels retained horizontally in each image can be calculated, such as Figure 3 As shown, the left border:

[0042] C Left =57.17

[0043] Right border:

[0044] C Right =1024-57.17=966.83

[0045] 6) According to the calculated left boundary C Left , right boundary C Right , crop each frame of the image, and the number of overlapping pixels between the two frames is The retained images are then subjected to subsequent processing such as image stitching and target detection.

[0046] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An image processing method based on an infrared array search system, the method comprising the following steps: 1) The infrared array search system collects N frames of images in one circle, and the field of view at the center of each frame is taken as the effective field of view angle fov e : 2) A single frame image has X pixels in the horizontal direction, and its azimuth field of view is fov x , calculate the number of overlapping pixels per frame image as D x : 3) When the device is horizontal, the pitch angle baseline value is The azimuth field of view size at this time is the field of view size set by the device, recorded as: The number of overlapping pixels is calculated by the above formula when the device is horizontal. 4) Read the current pitch angle baseline value: θ y , calculate the current azimuth field of view fov x : 5) The number of overlapping pixels when each frame image is kept horizontally is Crop both sides of each frame image, the number of pixels in the overlapping area of ​​the image remains unchanged, and the number of pixels C that need to be cropped on both sides of each frame image is calculated by the following formula x : 6) The number of cropped pixels C obtained by calculation x Calculate the pixel left boundary C retained horizontally for each image Left , right boundary C Right : C Left =C x (5) C Right =X-C x (6) 7) According to the calculated left boundary C Left , right boundary C Right , crop each frame of the image, and calculate the cropping area in real time so that the number of overlapping pixels of each frame of the image remains unchanged, which is The retained images are then processed.

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