Image Display Method Using State Marking Matrix for Sub-pixel Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing high resolution algorithms face challenges in completing an image conversion flow integrated with particular pattern processing without repetition or missing, especially in efficiently processing real pixels and considering previous processing results.
Innovation Solution
An image display method and apparatus that samples images row by row and column using a rectangular sampling area, comparing the image with preset characteristic patterns to determine gray scale values for monochromatic sub-pixels, marking them in a state marking matrix as unchangeable or changeable, ensuring that processing is done without repetition or omission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution algorithm is used to raise physical resolution to virtual resolution, then image resolution is improved, but processing complexity increases
Solution Approach 1:
The image processing is divided into distinct segments: characteristic pattern detection, gray scale value determination for matched patterns, and general processing for non-matched patterns. This segmentation allows the complex high resolution algorithm to be broken down into manageable steps, reducing overall processing complexity while maintaining high virtual resolution output
Solution Approach 2:
Characteristic patterns are pre-defined and stored before actual image processing begins. During processing, the algorithm performs preliminary detection to identify these pre-defined patterns, allowing for rapid gray scale value assignment without complex real-time calculations, thus reducing processing complexity while achieving high resolution
2Productivity
If particular pattern processing is integrated into image conversion flow, then processing efficiency is improved, but risk of repetition or missing pixels increases
Solution Approach 1:
A state marking matrix is implemented that provides feedback about the processing status of each pixel. The matrix tracks which pixels have been processed, which are pending, and which have determined gray scale values. This feedback mechanism ensures that no pixels are repeated or missed during the integrated processing flow, maintaining reliability while improving efficiency
Solution Approach 2:
The state marking matrix serves as an intermediary data structure between the characteristic pattern detection module and the general processing module. It coordinates the interaction between these modules, ensuring seamless integration of particular pattern processing into the overall image conversion flow without repetition or omission of pixels
3Manufacturing precision
If state marking matrix is used to track pixel processing status, then processing accuracy is improved, but memory requirements increase
Solution Approach 1:
The state marking matrix uses different marking states for different pixels based on their processing status. Rather than using a uniform data structure for all pixels, each pixel entry adapts its state (unprocessed, processed but gray scale value to be determined, gray scale value determined and unchangeable, gray scale value determined and changeable), optimizing memory usage while maintaining high processing accuracy
Solution Approach 2:
The marking values in the state marking matrix are changed as processing progresses. Pixels transition through different parameter states (from unprocessed to processed), allowing the system to track processing status efficiently with minimal memory changes rather than requiring complex data structures, thus balancing accuracy with memory requirements
Data Source
Figure 1
Figure 2~3A
Figure 3B
AI summary
Provided are an image display method and a display apparatus, wherein the method comprises comparing the image within the sampling area with each of the at least one preset characteristic pattern, respectively (101); when the image within the sampling area matches any of the at least one preset characteristic pattern, obtaining a gray scale value for at least one monochromatic sub-pixel among multiple monochromatic sub-pixels corresponding to the sampling area in a value assignment manner corresponding to the preset characteristic pattern, and marking the at least one monochromatic sub-pixel in a state marking matrix as gray scale value being determined and unchangeable (102); otherwise, calculating gray scale values for multiple monochromatic sub-pixels corresponding to the sampling area according to the markings of the multiple monochromatic sub-pixels corresponding to the sampling area in the state marking matrix and the image within the sampling area, and marking the monochromatic sub-pixels in the state marking matrix as gray scale value being determined and changeable or being processed but gray scale value to be determined (103). The present disclosure can complete an image conversion flow integrated with particular pattern processing in one traversal without repetition or missing.