GAN-Based GUI Layout Optimization for Artifact-Resistant Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing graphical user interface (GUI) rendering technologies inefficiently utilize processing and memory resources, particularly in devices with limited power and form factor, leading to increased resource consumption and reduced user experience due to visual artifacts from aggressive lossy compression.
Innovation Solution
A method and system for generating an alternative GUI with improved compressibility by utilizing a generative adversarial network (GAN) to optimize the layout and graphical elements, allowing for higher compression ratios without significant visual degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If aggressive lossy compression is applied to GUI rendering, then processing and memory resources are reduced, but visual quality deteriorates with artifacts appearing
Solution Approach 1:
The system performs preliminary actions by generating alternative GUI layouts and pre-compressing them to different quality levels before runtime. Compression metrics are calculated in advance, and the most efficient pre-compressed version is selected for rendering, avoiding the need for real-time compression decisions during execution.
Solution Approach 2:
The system changes parameters by generating multiple versions of the same GUI with different compression parameters (quality levels, block sizes). By adjusting these parameters and evaluating their compression ratios, the system identifies the optimal balance between resource efficiency and visual quality for each specific GUI element.
2Productivity
If compression ratio is increased to save resources, then processing efficiency improves, but visual artifacts increase and user experience deteriorates
Solution Approach 1:
The system evaluates multiple compression parameter configurations (different quality levels, block dimensions) and selects the parameter set that achieves the highest compression ratio while maintaining visual quality above a threshold, thus optimizing both processing efficiency and user experience.
Solution Approach 2:
The system incorporates feedback mechanisms by calculating compression metrics for alternative GUIs and using this information to select the optimal version. The feedback loop ensures that compression decisions are data-driven, balancing resource savings with maintained visual quality to preserve user experience.
3Use of energy by moving object
If alternative GUI generation is performed to improve compressibility, then resource utilization improves, but system complexity increases
Solution Approach 1:
The complexity of generating and evaluating alternative GUIs is shifted to a preliminary offline phase. During runtime, the system simply selects from pre-evaluated options, reducing the computational burden and complexity during actual operation while still achieving resource utilization benefits.
Data Source
AI summary
A system and method for improved compression of a graphical user interface (GUI) receives a first graphical user interface (GUI), the GUI including a GUI object. The method further includes compressing the first GUI, wherein the compressed first GUI is associated with a first compression ratio; generating a second GUI based on the GUI object of the first GUI, wherein the second GUI is different from the first GUI; compressing the second GUI, wherein the compressed second GUI is associated with a second compression ratio; generating an instruction which when executed configures a computer device to render the second GUI, in response to determining that the second compression ratio is higher than the first compression ratio; and generating an instruction which when executed configures the computer device to render the first GUI, in response to determining that the second compression ratio is lower than the first compression ratio.