ROI Image Encoding with Dual Encoders for Compact Reconstruction
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Solution Overview
Problem
Existing image and video processing methods are inefficient and inflexible, requiring substantial effort to change or optimize, and often rely on application-specific semantics, limiting their applicability and requiring the entirety of the input signal for reproduction.
Innovation Solution
A method involving a scene identity encoder and a structure extraction encoder processes pixel data to generate compact representations of a region of interest, using learnable encoders to derive structural features without application-specific semantics, allowing for photorealistic approximations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing image and video processing methods are used, then the original image or video data can be reproduced, but the amount of data transferred, stored, and processed is large and inefficient
Solution Approach 1:
The patent segments the image data processing into two independent encoders: a scene identity encoder that captures invariant scene element identifiers and a structure extraction encoder that captures visual characteristics. This segmentation allows each encoder to process specific aspects of the image separately, creating compact representations that reduce data quantity while maintaining reproduction quality through the combination of both encoders' outputs.
Solution Approach 2:
The patent extracts only the essential information from the original image data by using two encoders that process the image to generate compact data structures. The scene identity encoder extracts invariant identifiers for scene elements, while the structure extraction encoder extracts visual characteristics. This extraction approach removes redundant data while preserving the necessary information for high-quality reproduction.
2Adaptability or versatility
If application-specific semantics are used in processing methods, then the methods can be optimized for specific domains, but the methods become inflexible and require substantial effort to change or optimize
Solution Approach 1:
The patent creates a universal image processing system using two encoders that can handle multiple domains and applications without requiring domain-specific optimization. The scene identity encoder and structure extraction encoder work together to process various types of images across different domains, providing a flexible and adaptable system that reduces the need for substantial optimization effort for each specific application.
3Quantity of substance
If the entirety of the input signal is required for reproduction, then complete information is preserved, but data efficiency is reduced and processing becomes less flexible
Solution Approach 1:
The patent segments the image processing into two independent encoders that can process the input signal separately and generate compact representations. The scene identity encoder processes scene element identification while the structure extraction encoder processes visual characteristics. This segmentation enables the system to achieve complete information preservation through the combination of both encoders while significantly reducing data requirements and processing flexibility compared to processing the entire input signal as a whole.
Data Source
AI summary
A method of processing image data is provided. Pixel data for a first image is preprocessed to identify a subset of the pixel data corresponding to a region of interest depicting a scene element. The subset of the pixel data is processed at a first encoder to generate a first data structure representative of the region of interest, the first data structure identifying the scene element depicted in the region of interest. The subset of pixel data is also processed at a second encoder to generate a second data structure representative of the region of interest, the second data structure comprising values for visual characteristics associated with the scene element. The first and second data structures are outputted for use by a decoder to generate a second image approximating the region of interest of the first image.