Image processing method, image display method and electronic device

By combining AI multimodal intelligent agents and graph-based models, an automated closed-loop workflow is constructed, which solves the problems of high cost and low efficiency caused by the reliance on manual image processing in existing technologies, and realizes efficient and intelligent image processing and optimization.

CN122176092APending Publication Date: 2026-06-09RAJAX NETWORK &TECHNOLOGY (SHANGHAI) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
RAJAX NETWORK &TECHNOLOGY (SHANGHAI) CO LTD
Filing Date
2026-01-30
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

In existing technologies, image processing relies on manual processing, resulting in high labor and time costs, and the quality of image processing depends on the skill level of the designers, which cannot meet the needs for efficient and accurate processing.

Method used

By introducing AI multimodal intelligent agents, an automated closed-loop workflow of analysis-planning-execution-evaluation is constructed. The graph-to-graph model is used to autonomously analyze, plan and execute image processing tasks, and automated and intelligent image processing is achieved through evaluation and iterative optimization.

Benefits of technology

It realizes the transformation from "toolchain" thinking to "intelligent agent" thinking, lowers the threshold for users to use image processing tools, is suitable for batch image processing, realizes unattended automated optimization of massive images, and improves image quality.

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Abstract

Embodiments of the present application provide an image processing method, an image display method and an electronic device, and relate to the technical field of image processing. The image processing method comprises: inputting first image data into a first model, analyzing an original image in the first image data by the first model to obtain image structure information of the original image; generating first task description information corresponding to the original image according to the image structure information; the first task description information is used to represent a processing mode of the original image; inputting second image data into a second model, the second image data comprising the original image and the first task description information, so that the second model processes the original image according to the first task description information to obtain a target image. The present application realizes an automatic image processing flow from autonomous perception, planning to execution, and improves the image processing efficiency and quality.
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