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

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...

AI Technical Summary

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, which cannot fully achieve The effect of real-time processing

For UAV reconnaissance images with a large amount of data, it is more difficult to achieve the effect of real-time image processing by changing the parameters of the SIFT algorithm

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