An image processing method and device

Abstract

The embodiment of the present invention discloses an image processing method and device, which are applied to a system based on the integrated architecture of a field programmable gate array FPGA and a central processing unit CPU. The method includes: sending the image source data to be processed to the FPGA image processing intellectual property Core IP core: the FPGA image processing IP core performs image processing operations on the received image source data, and returns the obtained image processing result data to the application unit. Through the technical scheme of the invention, the speed of image processing tasks is improved for the system with integrated architecture of field programmable gate array FPGA and central processing unit CPU.

Description

technical field [0001] The present invention relates to image processing technology, and in particular, to an image processing method and device. Background technique [0002] The image processing task that Android (a Linux-based free and open source operating system) application needs to perform is a typical computing-intensive task, which takes a long time and is the bottleneck of Android application performance. [0003] The existing Android image processing acceleration scheme mainly uses GPU technology, but the GPU only supports some native instructions after the manufacture is completed. If there are operations that are not supported by the GPU instructions in the computing task, the CPU has to be used for computing, resulting in a decrease in computing efficiency. [0004] With the development of FPGA technology, there have been many hardware products that integrate FPGA and CPU. FPGA (Field-Programmable Gate Array, Field Programmable Gate Array) is a reconfigurable ...

AI Technical Summary

Problems solved by technology

[0002] The image processing task that Android (a free and open source operating system based on Linux) application program needs to perform is a typical computationally intensive task that takes a long time and is the bottleneck of Android application program performance.

[0003] The existing Android image processing acceleration solution mainly uses GPU technology, but after the GPU is manufactured, it only supports some native instructions. If the calculation task has an operation that the GPU instruction does not support, it has to use the CPU to calculate, resulting in a decrease in calculation efficiency.

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