Digital Camera Distortion Correction via Reduced Image Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing methods require multiple interpolation operations to correct trapezoidal distortion in images, leading to increased processing time and image degradation.
Innovation Solution
An image processing apparatus that acquires a reduced image, extracts distortion information, and performs projection transformation using projection parameters to correct trapezoidal distortion, reducing the number of operations and improving processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If pixel interpolation is performed twice (in image extraction and projection correction), then distortion correction is achieved, but image degradation increases and processing time increases
Solution Approach 1:
The patent performs distortion correction in advance during the image extraction phase by acquiring a reduced image and computing projection parameters. This preliminary correction eliminates the need for a second interpolation operation during projection correction, thereby reducing processing time while maintaining correction accuracy.
Solution Approach 2:
The patent segments the distortion correction process into two independent stages: (1) extracting a reduced image with distortion correction using projection transformation, and (2) using the projection parameters for subsequent processing. This segmentation allows the correction to be performed once during extraction rather than twice during both extraction and projection correction.
2Manufacturing precision
If pixel interpolation is performed twice (in image extraction and projection correction), then distortion correction is achieved, but image quality degrades
Solution Approach 1:
The patent performs distortion correction in advance during the image extraction phase by acquiring a reduced image and computing projection parameters. This preliminary correction eliminates the need for a second interpolation operation during projection correction, thereby reducing processing time while maintaining correction accuracy.
Solution Approach 2:
The patent segments the distortion correction process into two independent stages: (1) extracting a reduced image with distortion correction using projection transformation, and (2) using the projection parameters for subsequent processing. This segmentation allows the correction to be performed once during extraction rather than twice during both extraction and projection correction.
3Manufacturing precision
If distortion correction is performed for each pixel, then correction accuracy is improved, but the number of operations increases and processing time increases
Solution Approach 1:
The patent uses a reduced image (a copy of the original image at lower resolution) to extract distortion information and compute projection parameters. This copying approach allows distortion correction to be performed on a smaller dataset, reducing the number of operations required while maintaining correction accuracy for the full-resolution image.
Solution Approach 2:
The patent performs distortion correction in advance during the image extraction phase by acquiring a reduced image and computing projection parameters. This preliminary correction eliminates the need for a second interpolation operation during projection correction, thereby reducing processing time while maintaining correction accuracy.
Data Source
AI summary
A digital camera acquires the image of an original including an original from a shot image acquired by shooting. The digital camera reduces the image of the original and corrects distortion of the reduced image which is originated from the characteristic of a lens. As the digital camera performs distortion correction on the reduced image, the number of arithmetic operations in distortion correction is reduced, making distortion correction simpler. The digital camera acquires a rectangle defined by the contour of the original, extracts the image of the original to acquire an original image before reduction, and acquires an associated projection-transformed image by affine transformation. The digital camera acquires pixel positions of the original image using an affine parameter, and acquires pixel positions of the image before distortion correction using a relational expression of distortion correction performed on the reduced image.


