Time-Dependent Imagery Blending via Temporal Layering
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Solution Overview
Problem
Existing image mapping systems face challenges in efficiently processing and distributing time-dependent geographical imagery assets due to the complexity of handling assets with different resolutions and acquisition dates, leading to cumbersome processing and storage issues.
Innovation Solution
A method and system for processing and distributing time-dependent imagery assets by identifying available points in time for a geographical location, blending images captured at different times, and generating blended images that include secondary images from earlier times overlaid by primary images from the requested time, while also considering levels of detail and storage optimization using a processor and memory system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple images captured at different times are blended to show temporal changes, then the ability to represent time-dependent imagery is improved, but the processing complexity and storage requirements increase
Solution Approach 1:
The patent segments the blending process by separating temporal composition from spatial rendering. Images are pre-processed and stored as discrete temporal layers, which are then composited based on requested time points. This segmentation allows the system to handle time-dependent imagery without increasing the complexity of the core rendering pipeline.
Solution Approach 2:
The system performs preliminary actions by pre-processing images into standardized temporal layers during asset ingestion. Acquisition dates are embedded and images are organized into time-based sequences beforehand, so that when a request comes in, the system only needs to retrieve and composite pre-prepared layers rather than performing complex blending operations in real-time.
2Measurement precision
If images from multiple time points are stored and processed, then the accuracy of temporal representation is improved, but the storage requirements increase
Solution Approach 1:
The patent applies local quality by storing images at their native resolution and only processing/blending them at the specific time points and locations where they are needed. Rather than pre-computing and storing all possible temporal combinations, the system maintains temporal accuracy by keeping original images intact and performing localized blending operations only when requested.
Solution Approach 2:
The system changes parameters by storing images in a standardized format with embedded acquisition date metadata, then dynamically adjusting which temporal layers are composited based on the requested time point. This allows the system to maintain high temporal accuracy while optimizing storage by avoiding redundant pre-computed versions.
3Productivity
If chronological layering of images is implemented, then the retrieval efficiency is improved, but the device complexity increases
Solution Approach 1:
The patent adds a temporal dimension to the traditional spatial image organization. Images are arranged in chronological sequences alongside their spatial coordinates, creating a time-space indexing system. This allows the system to efficiently retrieve images by time point while maintaining the existing spatial rendering infrastructure, thus improving retrieval efficiency without fundamentally increasing system complexity.
Data Source
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AI summary
This specification describes a method, comprising identifying available points in time for which one or more images are available for a geographical location, selecting, with a processor, one of the one or more images associated with the geographical location, wherein the selected image includes portions of at least two different pieces of imagery of the geographical location, each of the at least two different pieces of imagery having been captured at different points in time, and providing the selected image to a client device for presentation on a display thereof.