Multi-Pixel Parallel Error Diffusion Processing
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Solution Overview
Problem
Current error diffusion methods in image processing are serial and cannot keep pace with high-speed parallel intensity information, leading to excessive processing rates and increased costs, especially when dealing with multiple pixels received in a single clock cycle.
Innovation Solution
A multi-pixel parallel error diffusion method that computes pixel values and updated error values simultaneously for multiple pixels in a single clock cycle, using a system of thresholds to determine binary pixel values and update error values efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If serial error diffusion method is used, then processing simplicity is maintained, but processing speed becomes insufficient for high-clock-rate parallel pixel data
Solution Approach 1:
The patent segments the error diffusion process into independent pixel-level operations that can be executed in parallel. Each pixel's error diffusion is calculated independently using the same threshold and error propagation rules, allowing simultaneous processing of multiple pixels without increasing system clock rate. This segmentation enables the processor to handle multiple pixels per clock cycle while maintaining correctness through systematic error propagation across segmented pixel regions.
Solution Approach 2:
The patent transitions from temporal processing (serial pixel-by-pixel processing over time) to spatial processing (simultaneous multi-pixel processing in parallel). By reorganizing the error diffusion calculations to operate across multiple pixels simultaneously in the spatial domain rather than sequentially in the temporal domain, the system achieves higher processing throughput without requiring increased clock rates or complex hardware architectures.
2Productivity
If increased processing rate is achieved through serial methods, then all pixel data can be processed, but system cost increases and clock rate requirements become excessive
Solution Approach 1:
The patent divides the pixel processing task into independent, parallelizable segments where each pixel can be processed simultaneously. This segmentation allows the system to achieve high productivity by processing multiple pixels in parallel within a single clock cycle, eliminating the need for excessive clock rates or complex hardware configurations that would increase system cost.
Solution Approach 2:
The patent changes the processing parameter from sequential time-based processing to parallel space-based processing. By reorganizing how pixels are processed (from one-by-one to multiple-at-once) while maintaining the same error diffusion algorithm logic, the system achieves improved productivity without requiring proportional increases in clock rate or hardware complexity, thereby keeping system costs manageable.
3Speed
If multiple pixels are processed in parallel, then processing speed increases, but maintaining correct error diffusion calculations becomes more difficult
Solution Approach 1:
The patent segments the error diffusion calculation into independent pixel-level operations that can be performed in parallel. Each pixel's error value is calculated independently based on its own intensity and the propagated error from previous pixels, maintaining calculation accuracy while enabling parallel processing. The systematic approach to error propagation ensures that parallel execution does not compromise precision.
Solution Approach 2:
The patent establishes a predetermined processing order and error propagation scheme before parallel execution begins. By pre-defining which pixels should receive error diffusion from which source pixels, the system ensures that parallel processing maintains correct calculations. The error diffusion threshold and propagation rules are established in advance, allowing parallel processors to follow consistent accuracy guidelines without coordination overhead.
Data Source
AI summary
A method and system for performing error diffusion are disclosed. An ordered set of pixels, including a pixel intensity value for each pixel, is received. Each pixel intensity value includes a value within a range from a low value to a high value, inclusive. An initial error value is also received. Based on the pixel intensity values and the initial error value, a pixel value for each pixel and an updated error value are computed substantially simultaneously with each other.