Vehicle Camera Image Appeal Enhancement via Semantic Analysis
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Solution Overview
Problem
Low-quality images captured by vehicle-mounted cameras for autonomous driving systems lack appeal and are not suitable for publication, despite being sufficient for analysis, due to cost constraints and competition among car manufacturers, with no existing automatic method to enhance their quality without requiring expensive hardware.
Innovation Solution
A method and system that automatically generates an appealing visual by processing the original image using semantic image content analysis, geometric parameter optimization, and post-processing techniques, incorporating information from other sources and databases to enhance and rectify the image, ensuring it meets predetermined criteria for appeal and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If cheap cameras are used for vehicle-mounted assistance systems, then cost is reduced, but image quality and appeal deteriorate
Solution Approach 1:
The patent replaces expensive high-quality camera hardware with a computational image processing system. Instead of improving image quality through better physical camera components, the invention uses software-based semantic analysis, geometric parameter optimization, and content adaptation to transform low-quality images into appealing visuals, thereby substituting mechanical/optical improvements with computational methods
Solution Approach 2:
The patent changes the parameters of the captured images through computational processing. It adjusts geometric parameters (perspective, distortion), semantic parameters (content selection, composition), and visual parameters (brightness, contrast, color) to transform low-quality images into high-quality appealing visuals, effectively improving image quality through parameter transformation rather than hardware upgrades
2Measurement precision
If vehicle-mounted cameras capture images optimized for assistance systems, then situation analysis accuracy is improved, but image appeal and publication suitability deteriorate
Solution Approach 1:
The patent segments the image processing task into two distinct phases: first, capturing images optimized for assistance system analysis with accurate semantic information; second, separately processing these images through semantic analysis, geometric optimization, and visual enhancement to create appealing publication-quality visuals. This segmentation allows each phase to optimize for its specific goal without compromise
Solution Approach 2:
The patent introduces an intermediary computational processing system that acts as a mediator between the raw camera output (optimized for analysis) and the final appealing visual. This intermediary performs semantic image analysis, identifies key content, adapts geometric parameters, and synthesizes a new image that satisfies both analytical accuracy and visual appeal requirements
3Ease of operation
If images are captured during vehicle movement, then convenience is improved, but image quality and stability deteriorate
Solution Approach 1:
The patent substitutes mechanical stabilization (tripods, fixed mounting) with computational stabilization methods. The system processes images captured during vehicle movement by analyzing semantic content, correcting geometric distortions, and applying post-processing techniques to compensate for motion-induced quality degradation, thereby achieving stable appealing visuals without physical stabilization equipment
Data Source
AI summary
A system and method for automatically generating an appealing visual based on an original visual captured by a vehicle mounted camera are provided. A semantic image content and its arrangement in the original visual is computed; an optimization process is performed that improves an appeal of the original visual by making it more similar to a set of predetermined traits. The optimization process may include adding information to the original visual to generate an enhanced visual by adapting content from further visuals, and adapting iteratively a geometric parameter set of the enhanced visual to generate a certain perspective or morphing to improve an arrangement of semantics in the enhanced visual. The optimized parameter set may be applied to the enhanced visual. Post-processing may be conducted after applying the optimized parameter set using a set of templates to generate a final visual that may be output for immediate or later use.