Adaptive Image Processing Strategy for Scene-Specific Imaging Quality
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing methods in imaging devices suffer from poor imaging effects due to lack of relevance in processing strategies, leading to suboptimal results in color adjustment, noise handling, edge sharpness, and inter-frame stability, particularly in diverse scenes.
Innovation Solution
An image processing method that selects strategies based on attribute information of the to-be-processed image, including global and local semantic attributes, temporal attributes, and alignment difficulty, using deep learning models for extraction and model selection to enhance image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed image processing strategy is used for all images, then the processing flow is simple and fast, but the imaging effect deteriorates in diverse scenes
Solution Approach 1:
The patent implements dynamic image processing by switching between different processing strategies based on scene characteristics. The system analyzes image attributes (such as brightness, contrast, noise levels) and dynamically selects the most appropriate processing strategy from multiple pre-defined strategies, making the processing flow adaptable rather than fixed, thus improving imaging效果 across diverse scenes while maintaining processing efficiency
Solution Approach 2:
The patent changes processing parameters based on image characteristics. Different processing strategies correspond to different parameter sets (e.g., different denoising strengths, different sharpening levels, different color adjustment parameters). By selecting strategies that match the image attributes, the system optimizes processing parameters dynamically, resolving the contradiction between fixed simple processing and high-quality imaging in diverse conditions
2Manufacturing precision
If multiple image processing strategies are prepared for different scenes, then the imaging effect is improved, but the system complexity increases
Solution Approach 1:
The patent prepares multiple image processing strategies in advance, with each strategy pre-configured for specific scene types (e.g., night scenes, bright scenes, high-contrast scenes). This preliminary preparation allows the system to quickly select from pre-optimized strategies rather than computing processing parameters in real-time, reducing the computational burden and system complexity while maintaining high imaging quality across different scenes
Solution Approach 2:
The patent applies different processing strategies to different regions or aspects of image processing based on local characteristics. Instead of applying a single global processing strategy, the system can select different strategies for different image regions or different processing stages (e.g., denoising for dark regions, sharpening for edge regions), reducing overall system complexity by applying complexity only where needed
3Ease of operation
If image processing is performed without considering specific image features, then the processing flow is simple, but color adjustment, noise handling, and edge enhancement quality deteriorate
Solution Approach 1:
The patent implements dynamic selection of processing strategies based on extracted image features such as brightness distribution, contrast levels, noise characteristics, and edge density. The system automatically adjusts the processing flow to match the image content, ensuring optimal color adjustment, noise handling, and edge enhancement for each specific image type while maintaining ease of operation through automated feature-based decision-making
Data Source
AI summary
An image processing method is provided. The method includes: obtaining a to-be-processed image; extracting attribute information of the to-be-processed image; determining an image processing strategy corresponding to the to-be-processed image according to the attribute information; and obtaining a target image by processing the to-be-processed image according to the image processing strategy.