Pixel Trapping Optimization via Luminosity Flags
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Solution Overview
Problem
Current raster-based trapping methods in printing are computationally expensive due to the need for pixel-by-pixel processing, leading to high computational costs and inefficiencies in eliminating white gaps and colored edges caused by misregistration.
Innovation Solution
A method that identifies frame buffer pixels as candidates for trapping by associating flags with pixels based on luminosity thresholds and object opacity, reducing the number of pixels processed by disregarding 'unpainted' pixels, which are perceptually equivalent to white, thereby optimizing the trapping process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If pixel-by-pixel trapping processing is performed to eliminate white gaps and colored edges, then print quality is improved, but computational cost increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing luminosity values for all pixels in the frame buffer before the trapping process begins. This preliminary computation eliminates the need for real-time luminosity calculations during trapping, significantly reducing the computational burden while maintaining the ability to accurately identify trapping candidates and eliminate white gaps and colored edges.
Solution Approach 2:
The patent segments the trapping process into two distinct phases: a preparation phase where luminosity values are pre-computed and stored for all pixels, and an execution phase where only pixels with set flags are processed for trapping. This segmentation separates the heavy computational work from the trapping operation itself, reducing the overall computational cost while preserving print quality.
2Measurement precision
If all pixels are processed as trapping candidates to ensure complete coverage, then trapping accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary action by pre-computing luminosity values and storing them in the frame buffer before trapping begins. During the trapping process, these pre-stored values are retrieved directly without recalculation, enabling accurate identification of trapping candidates while significantly reducing processing time compared to real-time computation.
Solution Approach 2:
The patent introduces an intermediary mechanism using flags associated with pixels that indicate whether a pixel should be processed as a trapping candidate. These flags act as a mediator between the full pixel data and the trapping algorithm, allowing the system to quickly identify and process only the relevant pixels that need trapping, thereby reducing processing time while maintaining accuracy.
3Reliability
If luminosity comparisons are performed for all pixels to identify trapping regions, then trapping reliability is improved, but computational overhead increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating luminosity values for all pixels and storing them in the frame buffer before the trapping process. This eliminates the need for complex real-time luminosity comparisons during trapping, reducing computational overhead while maintaining reliable identification of trapping regions through the pre-stored luminosity data.
Solution Approach 2:
The patent creates a copy of the frame buffer that includes pre-computed luminosity values and associated flags for each pixel. This copy serves as the working data structure during trapping, allowing reliable luminosity-based decisions to be made without the computational overhead of calculating luminosity values during the trapping process itself.
Data Source
AI summary
Methods disclosed permit the identification of frame buffer pixels for trapping. In some embodiments, flags associated with pixels in the frame buffer may be used to provide an indication of pixels for trapping. A bit in a flag associated with a pixel may be set when the pixel is painted, if the luminosity value of the pixel does not exceed a luminosity threshold. In some embodiments, the method discloses a process for updating the value of the bit through the rasterization process. The pixel may be identified as a candidate for trapping based on the value of the at least one bit at trapping time.