UAV Image Processing Texture Extraction for Navigation
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) inefficiently process images, leading to suboptimal decision-making in computer vision applications due to underutilization of information from various parts of captured images, particularly in binocular and monocular imaging systems.
Innovation Solution
A method and system that process both overlapping and non-overlapping portions of images from multiple imaging components with different fields of view to obtain texture information, allowing for improved environmental information acquisition and adjustment of imaging components for better decision-making in navigation and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If only overlapping portions of images are used for processing, then the processing complexity is reduced, but useful information from non-overlapping portions is lost
Solution Approach 1:
The patent segments the image processing task into distinct regions: overlapping portions are processed using binocular disparity methods, while non-overlapping portions are processed separately using monocular depth estimation and texture analysis. This segmentation allows each region to be handled with the most appropriate method, preserving useful information without requiring complex integration of all processing methods across the entire image.
Solution Approach 2:
The patent applies different processing qualities and methods to different parts of the image. Overlapping regions receive binocular processing for depth information, while non-overlapping regions receive monocular processing with enhanced texture analysis. This local quality approach ensures that each region is processed with the optimal method for its characteristics, maximizing information extraction while maintaining manageable complexity.
2Area of stationary object
If multiple imaging components with different fields of view are used, then the coverage area is increased, but the system complexity increases
Solution Approach 1:
The patent makes the imaging system universal by enabling each imaging component to serve multiple functions. The wide-field imaging component can operate independently for broad coverage or in conjunction with narrow-field components for detailed analysis. The system can adapt its configuration based on task requirements, using only the necessary components for each specific operation, thereby increasing coverage area while managing complexity through flexible, multi-functional design.
Solution Approach 2:
The patent implements dynamic configuration where the system can adjust which imaging components are active and how they are processed based on real-time requirements. The processor can dynamically select between processing only overlapping portions or also incorporating non-overlapping portions, and can adjust the level of detail processed in each region. This dynamic adaptability allows the system to expand coverage area while keeping complexity manageable by activating only necessary processing pathways.
3Measurement precision
If texture information from non-overlapping portions is processed, then environmental information accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by selectively processing only certain portions of non-overlapping regions based on their informational value. Rather than processing all non-overlapping portions with equal detail, the system identifies and processes only those regions containing useful texture information for depth estimation, while skipping or simplifying processing of redundant areas. This partial processing approach maintains environmental information accuracy while reducing overall processing time compared to exhaustive processing of all non-overlapping portions.
Data Source
AI summary
A system for processing images captured by a movable object includes one or more processors individually or collectively configured to process a first image set captured by a first imaging component to obtain texture information in response to a second image set captured by a second imaging component having a quality below a predetermined threshold, and obtain environmental information for the movable object based on the texture information. The first imaging component has a first field of view and the second imaging component has a second field of view narrower than the first field of view.