OS Image Processing Module Super-Resolution Optimization
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Solution Overview
Problem
Existing image processing in terminal devices often results in low resolution when displaying multimedia files, due to compression for bandwidth efficiency, leading to poor image quality and user experience.
Innovation Solution
An image processing method and device that includes an image optimization module within the operating system, which performs super-resolution processing on images based on their resolution and application permissions, using a task queue and multiple processors for efficient image optimization, ensuring higher definition images are displayed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If image compression is applied to reduce traffic during image display, then bandwidth efficiency is improved, but image resolution deteriorates
Solution Approach 1:
The patent segments the image processing into multiple layers with different resolution requirements. The first layer uses compressed low-resolution images for general display, while the second layer uses super-resolved high-resolution images for detailed viewing. This segmentation allows the system to optimize for both bandwidth efficiency and image resolution in different contexts.
Solution Approach 2:
The patent applies preliminary super-resolution processing to enhance image details before display. By pre-processing images to restore lost details through algorithms like bicubic interpolation or neural networks, the system prepares high-quality images in advance, allowing the display to present both compressed and enhanced versions as needed.
2Manufacturing precision
If super-resolution processing is performed to enhance image details, then image resolution is improved, but computation time increases
Solution Approach 1:
The patent applies partial super-resolution processing only when and where needed. Instead of processing all images at full resolution, the system selectively enhances images based on display requirements, user interaction, and content importance. This partial action approach reduces overall computation time while maintaining high resolution where most needed.
Solution Approach 2:
The patent dynamically adjusts the level of super-resolution processing based on real-time conditions. The system can switch between compressed and enhanced modes depending on network bandwidth, device performance, and user preferences, making the processing intensity adaptive rather than fixed.
3Adaptability or versatility
If image optimization is implemented at the operating system level, then adaptability across applications is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal image processing framework at the operating system level that serves multiple applications and functions. This single integrated system handles various image types, formats, and display scenarios, eliminating the need for separate optimization solutions in each application while maintaining broad adaptability.
Solution Approach 2:
The patent introduces an intermediary image processing layer between the application layer and display layer. This intermediary component handles all image optimization tasks centrally, acting as a mediator that simplifies the interface for applications while managing the complexity of super-resolution algorithms and compression techniques underneath.
Data Source
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AI summary
An image processing method and device are disclosed. The method is applicable to an image processing device having an operating system, and the method includes: receiving, by an image processing module of the operating system, an instruction of a first application program to call the image processing module of the operating system, where the instruction carries a to-be-displayed image and a resolution of the to-be-displayed image; and when the resolution of the to-be-displayed image is less than a first threshold, performing, by the image processing module, super-resolution processing on the to-be-displayed image, and displaying an image obtained after the super-resolution processing, to resolve a problem of a low image definition in a conventional display method.