yData compression processing method, device, equipment and webp compression system

Abstract

The invention discloses a method for compressing and processing YUV image Y data, which relates to the field of image processing, comprising: acquiring residual data of Y macroblocks of an input image; performing DCT transformation on the residual data of Y macroblocks to obtain AC coefficients; Add all sub-block data matrices in the residual data to obtain the DC component matrix of the macroblock residual data; perform WHT transformation on the DC component matrix to obtain the DC coefficient; quantize the AC coefficient and the DC coefficient to obtain the Y data compression data . This method can realize the parallel execution between DCT transformation and WHT transformation, improve the pipeline parallelism between modules, and improve the overall throughput performance of the WebP image lossy compression algorithm. The invention also discloses a YUV image Y data compression processing device, equipment and a YUV image-based WebP lossy compression system, which have the above beneficial effects.

Description

technical field [0001] The present invention relates to the field of image processing, in particular to a YUV image Y data compression processing method, device, equipment and a YUV image-based WebP lossy compression system. Background technique [0002] With the development of image acquisition equipment such as mobile phones, tablets, and digital cameras, and the increase in image pixel scale, the scale of Internet image data has grown exponentially. The latest research shows that from 2016 to 2021, the scale of data storage on data center servers will increase fourfold, from 663EB to 2.6ZB. Most of the data storage comes from images and videos, and image processing is used for data storage on data center servers. and network bandwidth will pose serious challenges. [0003] At present, in order to reduce the size of image storage, the image file format WebP with a higher compression rate is often used for storage. Compared with the JPEG lossy compression algorithm, the W...

AI Technical Summary

Problems solved by technology

[0006] From the Y macroblock residual data compression process, there is a data dependency between the sub-block DCT transformation and WHT transformation. After the DCT transformation of all 4x4 sub-blocks in the Y 16x16 macroblock is completed, the DC components of all sub-blocks can be generated. , and then the WHT transformation process of the DC component matrix can be started, resulting in that the DCT transformation and the WHT transformation can only be executed serially, and the deeply pipelined parallel WebP image lossy compression algorithm FPGA heterogeneous acceleration cannot be realized

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