Camera Image Conversion Using Precomputed Mapping Tables
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image conversion methods for camera images in surveillance systems are hindered by high processing time and complexity due to reliance on memory and computing resources, leading to delays in real-time display.
Innovation Solution
The method involves dividing the source image into sets of pixels that can be directly accessed from the processor's high-speed memory, such as registers or cache, and using a mapping table or homography matrix to perform coordinate conversions only on pixels requiring changes, thereby reducing the need for low-speed memory access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image distortion correction and visual angle conversion are performed using conventional methods, then image conversion accuracy is maintained, but processing time increases and real-time display is delayed
Solution Approach 1:
The patent divides the image processing into two distinct stages: (1) pre-computing and storing coordinate mapping relationships for pixels that require conversion, and (2) rapidly retrieving and applying these pre-computed mappings during real-time processing. This segmentation allows complex calculations to be performed offline, while online processing only requires simple lookups, thus resolving the contradiction between accuracy and speed.
Solution Approach 2:
The patent performs preliminary computation of coordinate mapping relationships before real-time processing. By pre-calculating and storing the mapping tables that define how each pixel coordinate transforms during distortion correction and visual angle conversion, the system eliminates the need for complex real-time calculations, achieving both high accuracy and real-time performance.
2Reliability
If conventional image conversion methods are used, then comprehensive image processing is achieved, but computational complexity increases
Solution Approach 1:
The patent pre-computes coordinate mapping relationships for all pixels that will require conversion, storing these mappings in lookup tables. This preliminary action transfers the computational burden from the real-time processing stage to an offline preparation stage, significantly reducing the computational complexity during actual image conversion while maintaining complete and accurate processing.
Solution Approach 2:
The patent creates pre-computed copies of coordinate mapping relationships and stores them in memory. Instead of performing complex coordinate transformation calculations repeatedly during real-time processing, the system simply retrieves and applies these pre-computed mapping copies, thereby reducing computational complexity while ensuring processing completeness.
Data Source
AI summary
A method of image conversion includes selecting a set of pixels from a source image, storing the set of pixels in a memory, determining whether the set of pixels includes at least one pixel requiring coordinate conversion by querying a predetermined mapping table, if the set of pixels includes the at least one pixel requiring coordinate conversion, converting the coordinates of the at least one pixel, and after converting the coordinates of the at least one pixel, removing the set of pixels from the memory.