Adaptive Image Resizing via Operational Feedback and Energy Functions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image resizing methods fail to adapt effectively to varying display types and network conditions, often degrading image quality when content is formatted for one display and viewed on another, and do not consider dynamic changes in channel quality or terminal parameters.
Innovation Solution
An image processing system that determines operational parameters associated with the communications channel and remote terminal, generates resized images using an energy function and seam carving techniques, and transmits them over the channel, while accounting for Quality of Service and terminal capabilities, using resizing templates to prioritize image content and features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images are formatted for a particular display type, then image quality is optimized for that specific display, but the image cannot be viewed effectively on other displays with different specifications
Solution Approach 1:
The patent implements dynamic image resizing by determining operational parameters from channel quality and terminal capabilities, then adjusting image dimensions and quality parameters in real-time. The system dynamically selects resizing algorithms and quality thresholds based on current network conditions and device specifications, allowing the same image to be optimized for different displays without manual intervention.
Solution Approach 2:
The system changes multiple image parameters simultaneously including resolution, quality threshold, and resizing algorithm selection based on operational parameters. By adjusting these parameters dynamically according to channel quality and terminal capabilities, the system achieves both adaptability across different displays and maintenance of optimal image quality for each specific display type.
2Manufacturing precision
If traditional resizing methods are used, then image format conversion is simple, but image quality degrades when viewed on different displays
Solution Approach 1:
The patent incorporates feedback mechanisms where the system continuously monitors channel quality parameters and terminal capabilities, then adjusts image processing parameters accordingly. This closed-loop feedback ensures that image quality is maintained by adapting processing complexity to actual conditions, avoiding unnecessary complex processing when network conditions or device capabilities allow for simpler methods.
Solution Approach 2:
The system performs preliminary determination of operational parameters before actual image processing occurs. By pre-assessing channel quality and terminal capabilities, the system prepares appropriate resizing parameters and algorithms in advance, reducing the complexity of real-time processing while maintaining high image quality through proactive optimization.
3Adaptability or versatility
If images are resized for mobile devices with limited specifications, then device compatibility is improved, but image quality deteriorates compared to original resolution
Solution Approach 1:
The patent applies different quality thresholds and resizing strategies to different regions or aspects of the image based on device capabilities. For devices with limited specifications, the system selectively optimizes critical regions while maintaining overall compatibility, ensuring that image quality is preserved in areas that matter most for the target display type while achieving necessary adaptability.
4Manufacturing precision
If high resolution images are transmitted over networks with limited bandwidth, then image quality is maintained, but transmission time and data consumption increase
Solution Approach 1:
The system dynamically adjusts image resolution and quality parameters based on real-time channel quality assessment. When network conditions indicate limited bandwidth, the system automatically reduces transmission resolution and adjusts quality thresholds to maintain acceptable image quality while minimizing transmission time and data consumption. This dynamic adaptation ensures optimal balance between quality and efficiency under varying network conditions.
Data Source
AI summary
An image processing system may include a transceiver configured to communicate with a remote terminal over a communications channel. Furthermore, an image processor may cooperate with the transceiver and be configured to determine an operational parameter associated with at least one of the communications channel and the remote terminal, generate a resized image from an original image based upon an energy function and the operational parameter, and transmit the resized image to the remote terminal over the communications channel.