Line-Based Radial Distortion Correction with Image Grid Mapping
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Solution Overview
Problem
Existing image distortion correction methods in electronic devices, particularly those using wide-angle lenses, are inefficient due to the difficulty in identifying user face regions, leading to prolonged processing times and varying quality or speed of correction based on image distance from the center.
Innovation Solution
An electronic apparatus and method that detects lines in an image to correct distortion by identifying target lines, performing distortion correction based on line positions and radial distortion, and updating grid maps to enhance correction efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If distortion correction is performed by identifying user face regions, then correction quality for facial areas is improved, but processing time becomes unnecessarily long when face identification is difficult or when there are many face regions
Solution Approach 1:
The patent segments the image into multiple grid cells and processes distortion correction at the grid level rather than requiring face region identification. Each grid cell is independently corrected based on its position and distortion characteristics, eliminating the need for time-consuming face detection while maintaining correction quality across the entire image.
Solution Approach 2:
The patent introduces a grid map as an intermediary structure that mediates between the distorted image and the correction process. The grid map provides a systematic framework for applying distortion correction without requiring direct identification of face regions, thus reducing processing time while maintaining correction effectiveness.
2Productivity
If distortion correction is performed based on image center without identifying face regions, then processing speed is improved, but correction quality decreases for portions farther from the center
Solution Approach 1:
The patent applies local quality by treating different grid cells differently based on their position and distortion characteristics. Each grid cell receives correction treatment tailored to its specific distortion degree, ensuring high correction quality across the entire image rather than applying uniform correction that would compromise quality for peripheral regions.
Solution Approach 2:
The patent transitions from correcting images based solely on distance from the center (one-dimensional approach) to a multi-dimensional approach using grid maps that consider both position and distortion characteristics. This dimensional expansion enables simultaneous optimization of both speed and quality across the entire image.
3Productivity
If batch image correction is performed, then processing efficiency is improved, but quality or speed of correction decreases
Solution Approach 1:
The patent segments the correction process into grid-based units that can be processed in parallel batches. Each grid cell is corrected independently using the same efficient algorithm, allowing batch processing to maintain both high efficiency and high quality. The segmentation enables parallelization without compromising the precision of individual correction operations.
Data Source
AI summary
An electronic apparatus including: a memory storing instructions; and at least one processor configured to execute the instructions, wherein, by executing the instructions, the at least one processor is configured to: acquire an input image, acquire line map information indicating positions of a plurality of lines in the input image, acquire two-dimensional (2D) grid map information including a plurality of grids corresponding to the input image, identify a target line intersecting the plurality of grids included in the 2D grid map information among the plurality of lines included in the line map information, identify a size of the target line, identify a degree of radial distortion of the target line based on the size of the target line, perform distortion correction on the target line based on the degree of radial distortion, and acquire a corrected image corresponding to the input image based on the distortion correction.