Dynamic Blue Component Resolution for Image Data Compression
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Solution Overview
Problem
Conventional image data compression methods fail to adaptively adjust color component resolutions based on dynamic conditions such as frame rate, change in image data, or user focus, leading to inefficient data transmission and potential loss of image quality.
Innovation Solution
A method that dynamically reduces the resolution of the blue component relative to red and green components in image data, transmitting error correction information to restore the blue component during display, with adjustments based on frame rate, change in image data, or user focus, thereby optimizing data transmission without significantly impacting user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the resolution of the blue component is reduced to improve data compression efficiency, then data transmission efficiency is improved, but image quality deteriorates
Solution Approach 1:
The patent applies dynamics by making the blue component resolution adaptive rather than fixed. The system dynamically adjusts the blue component resolution based on real-time conditions including frame rate, motion detection results, and scene complexity. When frame rate is high or motion is detected, blue resolution is reduced more aggressively; when frame rate is low or scene is static, blue resolution is maintained at higher levels. This dynamic adjustment resolves the contradiction by allowing image quality to fluctuate within acceptable bounds while prioritizing data transmission efficiency when needed.
Solution Approach 2:
The patent changes the resolution parameter of the blue component based on multiple conditional parameters including frame rate thresholds, motion detection results, and scene complexity metrics. The system monitors these parameters and adjusts the blue component bit depth accordingly (e.g., reducing from 8-bit to 4-bit or 2-bit representation). This parameter-based adaptation allows the system to optimize data transmission efficiency without permanently degrading image quality, as the parameter can be adjusted up or down based on conditions.
2Productivity
If the blue component resolution is reduced dynamically based on frame rate, then data compression efficiency is improved, but color accuracy deteriorates
Solution Approach 1:
The patent applies local quality by differentiating the treatment of the blue component from other color components. Instead of uniformly reducing all color component resolutions, the system specifically targets the blue component for resolution reduction while maintaining higher resolution for red and green components. This is based on the understanding that human visual sensitivity to blue is lower than to red and green, especially in peripheral vision. The local quality principle allows the system to compress blue data more aggressively while preserving overall color accuracy where it matters most to human perception.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring frame rate, motion detection results, and scene complexity, then using this feedback to adjust blue component resolution. The feedback loop ensures that color accuracy is maintained within acceptable bounds by adjusting compression levels based on actual viewing conditions and scene characteristics.
3Quantity of substance
If the resolution of the blue component is reduced to optimize transmission, then bandwidth utilization is improved, but visual fidelity deteriorates
Solution Approach 1:
The system dynamically adjusts blue component resolution based on real-time bandwidth requirements and scene characteristics. When bandwidth is constrained or frame rate is high, the system reduces blue resolution to maximize bandwidth utilization. When bandwidth is abundant or scene is static, blue resolution is increased to maintain visual fidelity. This dynamic behavior resolves the contradiction by allowing bandwidth utilization to take precedence when needed while preserving visual fidelity when possible.
Solution Approach 2:
The system changes the blue component resolution parameter based on bandwidth utilization metrics and scene complexity. By adjusting this parameter dynamically, the system can optimize bandwidth utilization during high-motion or high-frame-rate scenarios while maintaining visual fidelity during low-motion or low-bandwidth scenarios.
4Manufacturing precision
If error correction information is transmitted to restore the blue component, then image quality is improved, but data transmission overhead increases
Solution Approach 1:
The system transmits error correction information at reduced resolution levels for the blue component, changing the parameter of correction data granularity. Instead of transmitting full-resolution correction data for blue, the system transmits correction information at the reduced resolution level (e.g., 4-bit or 2-bit), which significantly reduces data transmission overhead while still enabling effective restoration of blue component quality during display.
Data Source
AI summary
A method of compressing image data involves determining an active area of an image to be displayed, at least part of which changes from frame to frame to provide a moving image. Color values for each pixel in at least part of the active area that has changed are determined (S73) and a resolution of a blue component of the color values is dynamically reduced (S75) relative to resolutions of green and red components of the color values. The image data is then transmitted, together with error correction information indicating how to correct the blue component when the image data is displayed. The active area may be a particularly fast changing part of the image or an area on which a user is focused.