Multi-channel image stitching method, system, readable storage medium, and unmanned vehicle

Abstract

The present disclosure relates to a multi-channel image stitching method, system, readable storage medium, and unmanned vehicle. The method is applied to a field programmable gate array platform, and the method includes: for each of the multiple images to be stitched , perform the following processing to obtain multiple rows of line buffer data for each path in the multiple paths of images to be spliced: repeatedly execute the acquisition of row data, and write the pixel data included in the row data into the path based on a preset mapping table The line buffer corresponding to the image to be spliced, the process of obtaining the line buffer data, until the first preset condition is met, the multiple lines of the line buffer data of the image to be spliced ​​are obtained; the multiple lines of the image to be spliced Write the multiple lines of line buffer data of each path into the frame buffer, and perform filling processing on the multiple lines of line buffer data of each path of the image to be spliced ​​to obtain spliced ​​frame buffer data; Perform preprocessing to obtain stitched images.

Description

technical field [0001] The present disclosure relates to the technical field of vehicles, and in particular, relates to a multi-channel image stitching method and system, a readable storage medium, and an unmanned vehicle. Background technique [0002] At present, in the field of unmanned vehicles, the vehicle surround view system is widely used in automatic driving and remote control driving to assist the driver in driving safely. For the automatic driving system, the surround-view perspective can improve the full-coverage obstacle detection capability. For remote remote control driving, the surround-view perspective can maximize the assistance of remote control driving to remove people from the scene and minimize the ratio of people to vehicles. [0003] In the related technologies, most of the vehicle surround view systems use pure software algorithms to realize multi-channel image stitching, and there is a bottleneck in stitching performance. It is impossible to achieve ...

AI Technical Summary

Problems solved by technology

[0003] In related technologies, most of the vehicle-mounted surround view systems use pure software algorithms to achieve multi-channel image stitching. There is a bottleneck in stitching performance, and it is impossible to achieve high frame rate and high-channel image stitching, and the stitched images are distorted and the stitching delay is high.

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