High-Resolution Image Storage via Selective Area Magnification
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Solution Overview
Problem
Current video compression algorithms, such as MPEG 2 and MPEG 4, reduce the clarity and sharpness of images, making it difficult to identify critical details like license plates and facial features, especially when compressing large volumes of video data for long-term storage in police car cameras.
Innovation Solution
The method involves capturing images, locating areas of interest, digitally magnifying these areas, and combining them with the original image data before compression to minimize the loss of clarity, thereby preserving high-resolution details during storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If compression algorithms are used to store large volumes of video data, then storage capacity is improved, but image clarity and detail identification are worsened
Solution Approach 1:
The patent segments the video processing into multiple stages: initial capture at full resolution, compression with reduced resolution, and post-compression enhancement of key areas. This segmentation allows different parts of the video data to be handled differently, preserving critical details while maintaining storage efficiency.
Solution Approach 2:
The patent performs preliminary identification of key areas during or after compression, then applies selective enhancement to those areas. This preliminary action of identifying what needs preservation allows the system to focus enhancement resources on critical regions rather than processing the entire compressed video uniformly.
2Productivity
If compression algorithms reduce resolution to store more video, then storage efficiency is improved, but the ability to identify critical details like license plates and facial features is worsened
Solution Approach 1:
The patent applies local quality enhancement by identifying specific key areas within the compressed video and enhancing only those regions. Different parts of the video receive different treatment: critical areas like license plates and faces are enhanced to high resolution, while other areas remain at compressed resolution, optimizing both storage efficiency and detail preservation.
Solution Approach 2:
The patent creates a copy of the original high-resolution video data and uses it selectively to enhance key areas in the compressed video. Rather than storing the entire high-resolution video, the system copies only the necessary portions to reconstruct critical details in the compressed output, reducing storage requirements while preserving essential information.
3Quantity of substance
If lossy compression is applied to reduce data volume, then storage requirements are improved, but visual quality that cannot be restored is lost
Solution Approach 1:
The patent performs preliminary identification of key areas before final compression or enhancement, marking regions that require quality preservation. This preliminary action allows the system to apply lossless or high-quality compression specifically to critical regions while allowing more aggressive compression in less important areas, maintaining reliability where it matters most.
Solution Approach 2:
The patent dynamically changes compression parameters based on the importance of different video regions. Critical areas use higher quality settings with less aggressive compression, while non-critical areas use lower quality settings. This parameter variation allows the system to reduce overall data volume while maintaining visual quality reliability in essential regions.
Data Source
AI summary
An image-creation method includes capturing an image as digital data, locating an area of interest of the captured image, extracting, from the digital data, at least some data corresponding to the located area of interest, digitally magnifying the extracted at least some data to yield digitally magnified data, and combining the digitally magnified data with at least some of the digital data of the captured image to yield combined data.