Homography Coordinate Mapping with Pixel Blocks for Faster Image Correction
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Solution Overview
Problem
Existing image correction methods based on homography transformation require a large quantity of computations, leading to long processing times and reduced applicability in timely and low-capability scenarios.
Innovation Solution
An image processing method that divides images into pixel blocks, determines mapping coordinates for a first pixel using a homography transformation formula, and calculates other pixel coordinates based on relative positional relationships within the block, reducing the need for repetitive homography transformations and utilizing Single Instruction Multiple Data (SIMD) technology for parallel interpolation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If homography transformation is applied to each pixel individually, then accurate image correction is achieved, but computation quantity increases and processing time lengthens
Solution Approach 1:
The image is divided into multiple pixel blocks, and within each block, only the first pixel undergoes homography transformation while other pixels use relative positional relationships. This segmentation approach reduces the number of homography transformations from N (total pixels) to N/B (blocks), where B is the average block size, significantly reducing computation while maintaining accuracy through local coordinate relationships.
2Loss of information
If homography transformation is applied to every pixel point, then complete mapping coordinates are obtained, but computation time increases
Solution Approach 1:
The method performs homography transformation on the first pixel of each block as a preliminary step, then uses relative positional relationships to derive coordinates of other pixels within the same block. This preliminary action approach ensures complete coordinate mapping while reducing computation time by avoiding repetitive homography transformations for pixels that can be derived through simpler relative position calculations.
3Reliability
If traditional interpolation methods are used, then image correction is performed, but computation requirements remain high
Solution Approach 1:
The method copies the homography transformation result from the first pixel of each block to other pixels through relative positional relationships, rather than performing independent homography transformations. This copying approach maintains image correction reliability by preserving local geometric relationships while significantly reducing computation energy by replacing complex matrix operations with simpler arithmetic calculations.
Data Source
AI summary
Disclosed are an image processing method and apparatus, an electronic device, and a storage medium. The image processing method determines mapping coordinates of a pixel point in a pixel block with one pixel block as a unit, and in this process, only a first pixel in the pixel block transformed through homography transformation based on a homography transformation formula to obtain projection coordinates thereof, and mapping coordinates of other pixel points (that is, second pixels) in the pixel block may be determined through a positional relationship between one of the plurality of second pixels and the first pixel in the pixel block. In this way, times of the homography transformation may be reduced, which is beneficial to reducing quantity of computation required by an entire image processing method and improving computation efficiency of the image processing method.