Wavelet Data Representation for Resolution-Independent Visualization
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Solution Overview
Problem
Current visualization technologies struggle to effectively represent large data sets at varying levels of resolution without significant loss of information or excessive processing resources, making it difficult to zoom in and out of data visualizations while maintaining accuracy.
Innovation Solution
The use of wavelet functions to transform data into reduced or expanded representations, allowing for efficient data reduction and restoration while preserving information density, enabling seamless transitions between detailed and less detailed views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If statistical methods are used to reduce data points for visualization, then the number of data points displayed is reduced, but information loss occurs and the ability to return to original presentation is compromised
Solution Approach 1:
The patent segments data into multiple resolution levels using wavelet decomposition, where each level represents a different degree of detail. This allows the system to display fewer data points at lower resolutions while preserving the ability to reconstruct and access higher-resolution representations, thus reducing information loss during visualization.
Solution Approach 2:
The patent implements a nested structure where reduced-resolution data representations are embedded within progressively higher-resolution representations. Each level contains information from the previous level plus additional detail, allowing seamless transition between resolutions without losing original information, similar to nested dolls where each contains the previous.
2Adaptability or versatility
If resolution of visualization is changed using conventional methods, then resolution adjustment is possible, but extensive processing resources are required
Solution Approach 1:
The patent performs wavelet decomposition and creates multiple resolution levels in advance before the user needs to view the data. This preliminary processing organizes data into a hierarchical structure that enables rapid resolution switching without requiring extensive processing at the time of visualization, as the transformation work has already been completed.
3Quantity of substance
If large data sets are visualized on limited resolution displays, then data points can be displayed, but significant reduction in detail availability occurs
Solution Approach 1:
The patent creates a dynamic visualization system where the resolution level can be adjusted on-the-fly based on user interaction and display capabilities. The wavelet-based structure allows the system to dynamically transition between different levels of detail, providing high detail when needed and reduced detail when appropriate, rather than being fixed at a single resolution level.
Data Source
AI summary
Methods and systems for representing data are disclosed. An example method can comprise providing a first representation of data and receiving a request to change resolution of the data. An example method can comprise, transforming, based on at least one wavelet function, the data to at least one of reduced data or expanded data. An example method can comprise providing a second representation of the data based on at least one of the reduced data or expanded data.