Automatic Image Enhancement via Reference Object Parameter Adjustment
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Solution Overview
Problem
Existing image and video processing techniques require manual supervision and user knowledge to enhance content appearance, especially for dramatic changes, which can be time-consuming and inefficient.
Innovation Solution
A method that selects a reference object in an image, determines image parameter adjustments based on predetermined criteria, and applies these adjustments to the entire image or video stream, using a priori knowledge to automatically enhance content appearance without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual supervision and user knowledge are used to enhance image content, then the quality of enhanced content can be improved, but the time consumption and operational complexity increase
Solution Approach 1:
The system automatically selects reference objects and determines image parameter adjustments without requiring manual user intervention. The computer identifies faces or foreground objects, applies predetermined face criteria, and autonomously enhances the entire image, eliminating the need for users to manually adjust parameters while maintaining high quality results
Solution Approach 2:
The system pre-establishes image parameter adjustment rules based on reference objects and predetermined criteria (such as face criteria based on other images of the same or different faces). These preliminary configurations enable automatic enhancement without requiring real-time manual supervision, reducing time consumption while preserving quality
2Manufacturing precision
If manual supervision is required to achieve desired image enhancement results, then the enhancement quality can be improved, but the ease of operation deteriorates
Solution Approach 1:
The system performs self-service by automatically selecting reference objects (faces or foreground elements), determining appropriate image parameter adjustments based on predetermined criteria, and applying enhancements without requiring users to possess image processing knowledge or manually intervene in the enhancement process
Solution Approach 2:
The system pre-configures enhancement parameters and criteria (such as face criteria derived from multiple images) before actual enhancement occurs. This preliminary preparation enables the system to automatically perform high-quality enhancement without requiring users to understand complex image processing concepts or manually adjust parameters
3Productivity
If automatic image enhancement is implemented, then the productivity is improved, but the manufacturing precision may deteriorate without manual supervision
Solution Approach 1:
The system uses feedback from reference objects (such as face detection results and foreground identification) to automatically determine appropriate image parameter adjustments. By continuously referencing predetermined criteria and comparing actual image characteristics against these standards, the system maintains high enhancement quality while operating automatically without manual intervention
Solution Approach 2:
The system pre-establishes comprehensive image parameter adjustment rules and criteria (including face criteria based on multiple images of the same or different faces) before enhancement. This preliminary configuration ensures that automatic enhancement maintains high precision by following pre-validated parameter settings, enabling both high productivity and manufacturing precision simultaneously
Data Source
AI summary
Implementations generally relate to enhancing content appearance. In some implementations, a method includes receiving an image, selecting a reference object in the image. The method also includes determining one or more image parameter adjustments based on the selected reference object, and applying the one or more image parameter adjustments to the entire image.