Hierarchical Image Tile Structure for Data Compression
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Solution Overview
Problem
Existing image processing technologies face challenges in efficiently updating and rendering high-definition images, particularly in reducing data size and achieving high-speed rendering, especially when parts of the image need to be updated.
Innovation Solution
The implementation of a hierarchical image data structure with quadtree organization, where images are divided into tile images of the same size across multiple layers, allowing for efficient switching and prefetching of data to manage image resolution changes, and a tile image reference table to identify redundant areas for data compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image data is stored with texture mapping for high-definition display, then rendering quality is improved, but data size increases and update complexity increases
Solution Approach 1:
The image data is divided into multiple layers with different resolutions (first layer, second layer, third layer, etc.), where each layer contains image data at a specific resolution level. This segmentation allows the system to store and process only the necessary resolution levels, reducing overall data size while maintaining high-definition rendering quality when needed.
Solution Approach 2:
The patent introduces a hierarchical dimension to image data storage by organizing data across multiple resolution layers. Instead of storing a single high-resolution image, the system stores progressive resolution levels, adding a resolution-dimension to the data structure that enables efficient memory usage and faster access times.
2Manufacturing precision
If high-resolution image data is stored for responsive display, then display quality is improved, but rendering speed decreases due to large data size
Solution Approach 1:
The system pre-processes and stores image data in multiple resolution layers in advance. When rendering is needed, the appropriate layer can be quickly selected and processed without requiring real-time compression or processing of high-resolution data, thus improving rendering speed while maintaining display quality.
Solution Approach 2:
The patent implements dynamic selection of image layers based on display requirements. The system can switch between different resolution layers depending on the current display context, allowing fast rendering when lower resolution suffices and high-quality rendering when necessary, thus optimizing rendering speed across different scenarios.
3Adaptability or versatility
If image data is updated after initial creation, then image content can be modified, but complex processing is required
Solution Approach 1:
By segmenting image data into discrete layers, the system allows updates to be applied to specific layers independently. When an image needs updating, only the affected layer or portions of layers need to be processed, rather than reprocessing the entire high-resolution image, thus reducing processing complexity while maintaining update capability.
4Quantity of substance
If data compression is applied to reduce file size, then storage efficiency is improved, but image quality may be degraded
Solution Approach 1:
The hierarchical layering allows the system to apply different compression strategies to different resolution levels. Lower layers can use more aggressive compression since they represent lower resolutions, while higher layers maintain better quality. This segmented approach reduces overall data size while preserving image quality where it matters most.
Data Source
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AI summary
An image hierarchy generation unit (120) of a controller (100b) reads image data stored in a hard disk drive (50) and generates and hierarchizes images having a plurality of resolutions. An image segmentation unit (122) segments images in respective hierarchies into tile images. A redundancy detection unit (124) analyzes the images in the respective hierarchies and detects redundancies of the images in the same hierarchy and between different hierarchies. A tile image reference table creation unit (126) creates a tile image reference table, in which region numbers and tile numbers are associated with each other, in consideration of the redundancies. An image file generation unit (128) generates an image file to be finally outputted, which includes image data and the tile image reference table.