Image processing method and device, equipment, computer storage medium, and system

Abstract

The embodiment of the invention discloses an image processing method and device, equipment, a computer storage medium, and a system. The method comprises the following steps: acquiring a plurality of reconstructed blocks, wherein the plurality of reconstructed blocks are obtained after a plurality of image blocks, divided by a to-be-processed image, pass through a preset coding network model and a preset decoding network model; determining a central region of at least one reconstructed block in the plurality of reconstructed blocks; performing quality enhancement on the central region of the at least one reconstructed block to obtain at least one target reconstructed block; generating a reconstructed image according to the at least one target reconstructed block and the plurality of reconstructed blocks; filtering block boundaries in the reconstructed image to obtain a target image.

Description

technical field [0001] The present application relates to the technical field of video coding and decoding, and in particular to an image processing method, device, equipment, computer storage medium and system. Background technique [0002] In recent years, artificial neural networks have developed to the stage of deep learning. Deep learning is a branch of machine learning. It is an algorithm that attempts to abstract data at a high level using multiple processing layers that contain complex structures or multiple nonlinear transformations. Its powerful expressive ability makes it widely used in computer vision and image processing. It has been widely used and has good performance in video and image processing. [0003] At present, image encoding and decoding and image post-processing technologies based on deep learning often adopt the scheme of inputting the entire image into the encoding and decoding network at one time for processing. However, as the size of the image...

AI Technical Summary

Problems solved by technology

However, as the size of the image increases and the codec network deepens, this solution will lead to a significant increase in the running time of the codec and the memory requirements for operation.

In addition, even though there are currently some block-based image encoding and decoding schemes, the structure of the existing schemes makes the encoding and decoding between blocks not completely independent, and the parallelization of encoding and decoding processing cannot be realized, and the running time of encoding and decoding cannot be reduced. and running memory requirements

Images