Video Conference Image Clarity via ROI Area Expansion
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Solution Overview
Problem
In group videoconferencing, the clarity of participant images is compromised due to reduced pixel allocation and lossy compression, leading to unclear and disorienting representations of spatial relationships among participants.
Innovation Solution
A videoconferencing unit processes images to enhance the proportion of region of interest (ROI) area by determining and reducing background regions, allowing for clearer ROI representation despite down-sampling and limited resolution, while preserving spatial relationships through cropping and geometric background compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the camera is zoomed out to capture all participants in group videoconferencing, then the coverage area increases, but the number of pixels dedicated to each participant decreases, reducing image clarity
Solution Approach 1:
The patent segments the image into regions of interest (participants) and background regions, applying different processing treatments to each segment. This allows the system to maintain high pixel allocation for participants while reducing background detail, thereby preserving image clarity for important areas while managing overall bandwidth requirements.
Solution Approach 2:
The patent applies local quality enhancement by selectively processing different regions of the image with different quality levels. Regions containing participants are maintained at high quality with sufficient pixels, while background regions are compressed more aggressively. This resolves the contradiction by ensuring local image clarity where needed while accepting reduced quality in less important areas.
2Loss of energy
If down-sampling and lossy compression are applied to reduce bandwidth, then transmission efficiency improves, but the clarity and detail of participant images deteriorate
Solution Approach 1:
The patent divides the image into participant regions and background regions, applying different compression strategies to each segment. Participant regions undergo milder compression to preserve clarity, while background regions receive more aggressive compression. This segmentation approach reduces overall bandwidth consumption while maintaining acceptable image quality for important areas.
Solution Approach 2:
The patent implements local quality control by applying differential compression ratios to different image regions. High-quality encoding is applied to participant areas to maintain clarity, while lower-quality encoding is applied to background areas. This resolves the bandwidth-clarity contradiction by optimizing quality distribution according to regional importance.
3Measurement precision
If multiple cameras are used to capture individual participants clearly, then image clarity improves, but device complexity and cost increase
Solution Approach 1:
The patent extracts and isolates participant regions from the full scene using image processing algorithms. By identifying and separating participant areas from the background through computational methods, the system achieves clear participant images using a single camera, eliminating the need for multiple cameras while maintaining image clarity.
Solution Approach 2:
The patent replaces the mechanical solution of using multiple physical cameras with a computational image processing approach. Instead of adding more hardware cameras to capture individual participants, the system uses software-based region extraction and selective enhancement techniques to achieve the same goal, thereby reducing device complexity while maintaining clarity.
4Loss of information
If the entire captured image is transmitted, then complete scene information is preserved, but transmission bandwidth and processing resources increase significantly
Solution Approach 1:
The patent segments the image into participant regions and background regions, transmitting different segments with different levels of detail. Participant regions are transmitted with high fidelity to preserve important scene information, while background regions are compressed more aggressively. This segmentation strategy reduces overall bandwidth consumption while maintaining essential scene information.
Solution Approach 2:
The patent applies local quality optimization by transmitting different quality levels for different image regions. High-quality transmission is applied to participant areas to preserve important information, while lower-quality transmission is applied to background areas. This resolves the contradiction by optimizing bandwidth usage according to the informational importance of different regions.
Data Source
AI summary
An image processing system processes images such that a proportion of area of regions of interest within the image can be increased at the expense of regions of lesser interest. First, regions of interest, such as portions of the image including participants, are determined. Then compressible background regions are determined and compressed. This results in the proportion of the area of the regions of interest to increase. After the image is stored or transmitted, the regions of interest can be seen more clearly both because they are larger and because any loss of detail caused by down-sampling or lossy image compression needed to limit the amount of image information is reduced due to the smaller image size. The process also preserves more of the relative spatial relationship between various regions of interest than prior methods.