Parallel Image Processing with Serpentine Scan Path
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Solution Overview
Problem
Existing halftoning processes in imaging devices, such as printers and scanners, face a trade-off between image quality and throughput, with methods like Tone Dependent Fast Error Diffusion (TDFED) producing high-quality halftone images but at lower production rates compared to parallel processing techniques.
Innovation Solution
Implementing a four-row serpentine scan path in conjunction with TDFED, where multiple rows of pixels are processed concurrently using a controller with processing circuitry like FPGA or ASIC, allowing for error diffusion across predetermined unprocessed pixel locations based on look-up tables, thereby increasing throughput while maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional serpentine order processing is used, then device complexity is reduced, but productivity decreases
Solution Approach 1:
The image data is divided into multiple bands, where each band contains a specific number of rows (e.g., four rows). This segmentation allows parallel processing of different bands simultaneously, increasing throughput while managing device complexity through modular organization of processing resources.
Solution Approach 2:
The patent transitions from sequential single-row processing to multi-row parallel processing by introducing a band-based structure. This dimensional change in processing organization enables multiple rows within each band to be processed concurrently, significantly improving productivity.
2Productivity
If parallel processing of multiple rows is implemented, then productivity increases, but manufacturing precision may deteriorate due to error diffusion challenges
Solution Approach 1:
Error diffusion look-up tables are pre-calculated and stored for each possible contone value (0-255). This preliminary preparation allows the parallel processing to quickly retrieve appropriate error diffusion values without real-time calculation, maintaining image quality while enabling high-speed parallel processing.
Solution Approach 2:
The patent replaces complex real-time error diffusion calculations with pre-computed look-up tables. This substitution eliminates the need for complex computational mechanisms during parallel processing, ensuring consistent image quality while maintaining high throughput.
3Manufacturing precision
If Tone Dependent Fast Error Diffusion is applied, then manufacturing precision is improved, but productivity decreases
Solution Approach 1:
The patent segments the image into bands of multiple rows that can be processed in parallel. This segmentation allows TDFED to be applied to multiple rows simultaneously rather than sequentially, maintaining the high image quality of TDFED while dramatically increasing the processing rate through parallel execution.
Solution Approach 2:
The patent combines TDFED algorithm with parallel band-based processing structure and look-up table methodology to create a composite processing system. This composite approach integrates the quality benefits of TDFED with the speed benefits of parallel processing, achieving both high image quality and high productivity.
Data Source
AI summary
In some examples, an imaging device may include a controller including processing circuitry to detect, a first quantity of rows of pixels to be included as a first band of a contone image, process the pixels of each row of the first band in parallel raster order, detect a second quantity of rows of pixels to be included as a second band of the contone image; and process the pixels of each row of the second band in response to the completion of the pixels of the first band, where the rows of the second band are processed in parallel in serpentine order with respect to the first band.