Synthesized Image Context Reconstruction via Procedural Inference
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Solution Overview
Problem
Existing image generation systems lack the ability to provide contextual information alongside areas of interest, which can limit the viewer's ability to interpret these areas effectively.
Innovation Solution
A system that generates synthesized images by combining areas of interest with a synthesized environment, using a procedural reconstruction process and a trained inference model to create a familiar context for interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If only areas of interest are stored and displayed, then storage efficiency and computational resources are improved, but contextual information is lost which limits interpretation ability
Solution Approach 1:
The patent segments the image into two distinct parts: areas of interest (AOI) and synthesized environment. The AOI contains the actual relevant content while the synthesized environment provides contextual background. This segmentation allows selective storage of only AOI in high-performance storage while generating context on-demand, resolving the contradiction between storage efficiency and information completeness.
Solution Approach 2:
The patent introduces a synthesized environment as an intermediary element that bridges the gap between limited AOI data and the need for contextual information. This synthesized environment is generated procedurally using inference models and stored in lower-performance storage, acting as a mediator that provides context without requiring storage of the entire original image.
2Loss of information
If synthesized environment is generated using procedural reconstruction, then contextual information is provided, but computational resources and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-generating and storing synthesized environments in lower-performance storage before they are needed. When AOI is retrieved from high-performance storage, the corresponding synthesized environment is already available or can be quickly generated from stored representations, reducing the computational burden at retrieval time and balancing the trade-off between information quality and processing resources.
3Loss of information
If high-performance storage is used for all image data, then interpretation ability is improved, but storage costs and resource usage increase
Solution Approach 1:
The patent applies local quality by assigning different storage performance levels to different parts of the image data. Areas of interest are stored in high-performance storage for rapid access, while synthesized environments providing contextual information are stored in lower-performance storage. This differentiated storage strategy optimizes the balance between interpretation ability and storage resource consumption by matching storage quality to the specific needs of each data component.
Data Source
AI summary
Methods and systems for obtaining synthesized images are disclosed. To obtain synthesized images, an imaging system may obtain areas of interest associated with an image. The areas of interest may be keyed to various processes and/or services. A downstream consumer of the services may retrieve the areas of interest to perform further analysis. In order to more easily interpret the areas of interest, the areas of interest may be displayed to the downstream consumer as part of a synthesized image. The synthesized image may include the areas of interest and a synthesized environment. The synthesized environment may be intended to emulate an environment in which the downstream consumer may expect to find the areas of interest. By doing so, the downstream consumer may be able to understand and contextualize the areas of interest more easily than if viewing the areas of interest alone.