High-resolution image accelerated processing method based on parallel pipeline mechanism

Abstract

The invention discloses a high-resolution image accelerated processing method based on a parallel pipeline mechanism. The method is realized by utilizing the FPGA parallel pipeline processing mechanism. The method comprises the following steps: S1) carrying out color interpolation on a RAW-format image generated through a Bayer color filter array (CFA) through a 3*3 template of a bilinear method to obtain RGB image data, and converting the RGB image data into a YUV color space and extracting a Y component therein to obtain a grayscale image; S2) removing spot noise in the grayscale image obtained in the step 1) through a median value filtering method; and S3) carrying out gray gradient calculation on each point on the grayscale image obtained after spot noise removing through a sobel operator, carrying out non-maximum suppression on gradient amplitude results and realizing edge thinning, and finally, carrying out binaryzation on the result thereof to extract edge information of the grayscale image. The advantages are that, by combining FPGA parallel processing and pipeline structure features and by utilizing Verilog DHL (hardware description language) to compile an image processing unit of the FPGA, high-efficiency high-speed execution of an image processing algorithm is realized.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an accelerated processing method for high-resolution images based on a parallel pipeline mechanism. Background technique [0002] Image processing technology is widely used in industrial production, engineering applications, aerospace, military, medical and many other fields, and has achieved great success and significant economic benefits. With the significant improvement of the resolution of image acquisition chips and the high With the continuous development of precision, high speed and high integration, the requirements for data processing speed are getting higher and higher. It is difficult for the image processing system using only DSP to meet the above requirements. [0003] In image processing, different levels and types of operations such as image summation, difference, gradient operation, target segmentation, and region feature extraction are often used. Among ...

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Problems solved by technology

[0002] Image processing technology is widely used in industrial production, engineering applications, aerospace, military, medical and many other fields, and has achieved great success and significant economic benefits. With the significant improvement of the resolution of image acquisition chips and the high With the continuous development of precision, high speed and high integration, the requirements for data processing speed are getting higher and higher. It is difficult for the image processing system using only DSP to meet the above requirements.

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