Drawing Apparatus Dynamic LUT Rewriting for Multi-Camera Image Quality
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Solution Overview
Problem
Existing drawing apparatuses face challenges in obtaining high-quality simulation results when generating composite images from multiple camera data, as they struggle to effectively utilize the characteristics of each camera lens, leading to missed areas and low image quality due to fixed camera mapping or nearest position-based processing.
Innovation Solution
A drawing apparatus and method that uses Look Up Table (LUT) data to perform coordinate conversion and alpha blending processing, while rewriting LUT data based on camera characteristics such as lens distortion, to select the highest quality image data for each pixel, ensuring optimal image quality without considering camera direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If image data is selected based on predetermined camera positions or nearest position processing, then processing is simplified, but image quality deteriorates and missed areas occur
Solution Approach 1:
The patent implements dynamic image data selection by calculating determination distances from the optical center for each pixel across multiple cameras and selecting the camera that provides the shortest distance (highest quality) for each pixel. This dynamic per-pixel selection replaces static predetermined mapping, resolving the contradiction between processing simplicity and image quality by automating the selection process through systematic distance calculations rather than manual configuration.
Solution Approach 2:
The patent changes the selection parameter from fixed camera position assignment to variable determination distance calculation. By using the distance from the optical center as the selection criterion, the system adapts the camera selection based on the specific pixel location and camera characteristics, thereby improving image quality while maintaining processing efficiency through mathematical calculations.
2Manufacturing precision
If complicated processing is performed to select image data based on 3D coordinates, then image quality improves, but processing complexity increases
Solution Approach 1:
The patent extracts only the essential parameter needed for image quality selection - the determination distance from the optical center - while discarding unnecessary 3D coordinate transformations and complex geometric processing. By focusing solely on the distance calculation in the image plane, the system achieves high image quality through simple 2D distance computations rather than complicated 3D processing.
Solution Approach 2:
The patent replaces complex mechanical 3D coordinate transformation systems with a simplified mathematical approach based on 2D distance calculations from the optical center. This substitution uses straightforward Euclidean distance formulas instead of complex 3D transformation matrices, reducing processing complexity while maintaining image quality selection accuracy.
3Productivity
If fixed camera mapping areas are used, then processing is simplified, but missed areas and low image quality occur
Solution Approach 1:
The patent replaces fixed static camera mapping areas with dynamic per-pixel camera selection based on determination distance calculations. For each pixel in the composite image, the system dynamically determines which camera provides the best quality data by calculating the distance from that pixel to each camera's optical center, ensuring complete coverage and high quality without missed areas.
Solution Approach 2:
The patent implements a feedback mechanism where the determination distance calculation provides information about image quality for each pixel, and this feedback is used to select the optimal camera source. The system continuously evaluates and selects the best camera for each pixel based on the calculated distances, ensuring complete and high-quality image composition without fixed mapping limitations.
Data Source
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AI summary
A drawing apparatus includes a first control unit and a second control unit. The first control unit receives a plurality of image data including a subject from a plurality of cameras, and outputs data obtained from coordinate conversion performed by referring to LUT data. The second control unit derives each of determination distances from optical centers of the plurality of image data with regard to the subject, selects one of the plurality of image data as selection image data on the basis of the determination distance, and rewrites the LUT data by deriving a coordinate corresponding to a pixel of the subject in the selection image data.