Dynamic Image Quality Mapping for Transcoding Resource Optimization
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Solution Overview
Problem
Current image transcoding methods result in large data volumes due to high quality configurations, leading to wastage of storage and network resources, as they often fail to match the quality configuration of the source image during transcoding to the target image format, causing redundancy and distortion.
Innovation Solution
An image transcoding method that dynamically uses a corresponding quality configuration based on the source image's quality parameter to transcode images into a target format, ensuring minimal data volume and maintaining image quality by matching or mapping the quality parameters between source and target formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a relatively high quality configuration is used during image transcoding, then image quality is improved, but data volume increases leading to waste of storage and network resources
Solution Approach 1:
The patent dynamically adjusts the target quality parameter based on the source quality parameter through a mapping relationship. Instead of using a fixed high quality configuration, the system changes the quality parameter according to the actual source image characteristics, achieving optimal balance between image quality and data volume reduction.
2Manufacturing precision
If a fixed high quality configuration is used for all source images, then image quality is maintained, but storage and network resources are wasted due to unnecessarily large file sizes
Solution Approach 1:
The patent transforms the static fixed quality configuration into a dynamic adaptive configuration. The target quality parameter is no longer fixed but dynamically determined by the mapping relationship with the source quality parameter, allowing the system to adapt to different source images and avoid unnecessary resource consumption.
Solution Approach 2:
The system changes the quality parameter from a fixed constant to a variable that depends on the source image characteristics. By establishing a mapping relationship between source and target quality parameters, the system optimizes the balance between maintaining image quality consistency and reducing resource waste.
3Device complexity
If quality parameter mapping between source and target formats is not performed, then transcoding simplicity is maintained, but image quality deteriorates and data volume increases
Solution Approach 1:
The patent performs preliminary determination of the target quality parameter by establishing a mapping relationship with the source quality parameter before the actual transcoding process. This preliminary action ensures that the appropriate quality configuration is selected in advance, preventing image quality deterioration and unnecessary data volume increase during transcoding.
Data Source
AI summary
Embodiments of this application disclose an image transcoding method performed at a computing device. The image transcoding method includes: obtaining a source image quality parameter of a source image, the source image being a to-be-transcoded image, and the source image quality parameter being associated with a source image format and used for indicating image quality of the source image; obtaining, according to the source image quality parameter and a preset mapping relationship, a target image quality parameter that is associated with a target image format and that corresponds to the source image quality parameter of the source image; and transcoding the source image in the source image format according to the target image quality parameter to obtain a target image in the target image format.