Parallel and matching precision constrained splicing method for consecutive frames of multi-feature-point unmanned aerial vehicle reconnaissance images

A technology with precision constraints and feature points, applied in image enhancement, image analysis, image data processing and other directions, it can solve the problems of difficulty in real-time image processing, not fully achieving real-time processing, and not much improvement in image stitching speed. Excellent stitching effect, accurate registration, and the effect of improving processing speed

Inactive Publication Date: 2014-06-25
BEIHANG UNIV
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Problems solved by technology

Although this algorithm brings a good registration effect to image registration, it does not improve the image stitching speed much. Most scholars improve the speed index from the parameter configuration of the SIFT algorithm, whic...

Method used

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  • Parallel and matching precision constrained splicing method for consecutive frames of multi-feature-point unmanned aerial vehicle reconnaissance images
  • Parallel and matching precision constrained splicing method for consecutive frames of multi-feature-point unmanned aerial vehicle reconnaissance images
  • Parallel and matching precision constrained splicing method for consecutive frames of multi-feature-point unmanned aerial vehicle reconnaissance images

Examples

Experimental program
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Embodiment

[0064] In this example, a 4-core computer is used to test 88 frames of UAV remote sensing images. The test process and results are as follows:

[0065] The first step: assign task blocks, create threads, and extract image SIFT feature points.

[0066] 1) Read in the storage path of the images to be spliced, and count the number n=88 of the images to be spliced;

[0067] 2) According to the number of images n and the number of processor cores k=4, divide the images to be spliced ​​into blocks, that is, divide the images to be processed into k groups on average. Ideally, the number of images in each group should be equal, which is n / k images.

[0068] 3) Create threads according to the number of assigned task blocks. The created k threads work in parallel at the same time, and are used to extract the feature points of the images in the corresponding task blocks. The feature points of two single images are as follows: Figure 4a , 4b shown.

[0069] During the test, 1, 2, 4,...

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Abstract

The invention discloses a parallel and matching precision constrained splicing method for consecutive frames of multi-feature-point unmanned aerial vehicle reconnaissance images, and belongs to the technical field of unmanned aerial vehicle image processing. According to the method, the data sizes of four stages, namely, the feature extraction sage, the feature matching stage, the matrix transformation stage and the image synthesis stage, of image splicing are deeply analyzed, and the serial or parallel dependence relations between the stages are deeply analyzed. The data processing mode which conforms to the large-data-size image processing features of an unmanned aerial vehicle and meets the requirement for processing the features of the unmanned aerial vehicle is designed according to types of data and relations between the data. Meanwhile, a multi-core resource and multi-thread calculation method of a computer is applied to the data processing process so that the use ratio of computing resources can be increased and the operation speed can be increased. The method is high in pertinence, the capacity for splicing and processing the large-data-size remote sensing images of the unmanned aerial vehicle can be remarkably improved, and real-time generation of image splicing intelligence of the unmanned aerial vehicle is ensured.

Description

technical field [0001] The invention belongs to the technical field of UAV image processing, and in particular relates to a splicing method using continuous frame multi-feature point UAV reconnaissance image parallelism and matching precision constraints. Background technique [0002] UAV reconnaissance technology is a kind of remote sensing technology, which has its own advantages compared with satellite reconnaissance, such as low cost, flexible reconnaissance area control, no access time and cycle restrictions, and high resolution of ground targets; compared with manned reconnaissance aircraft, It has the advantages of continuous work day and night, regardless of pilot fatigue and casualties. In recent years, due to the advantages of high resolution, high flexibility, high efficiency and low cost of low-altitude remote sensing data, UAVs have been widely used in natural disaster area assessment, battlefield reconnaissance, environmental monitoring and other fields. For e...

Claims

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Application Information

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IPC IPC(8): G06T5/50G06T3/40G06T7/00
Inventor 丁文锐袁永显李红光向锦武刘硕
Owner BEIHANG UNIV
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