Page Data Compression Hardware With Interleaved Color Planes
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Solution Overview
Problem
Current compression and decompression techniques fail to provide satisfactory results, especially when handling image data, as loss-less algorithms perform poorly on images and lossy algorithms degrade text data, while mixed approaches are slow and complex, reducing data processing speeds and compression ratios.
Innovation Solution
A hardware implementation that interleaves color plane data and uses a compressor/decompressor system with independent modules for run, seedrow copy, and literal operations, enabling efficient compression and decompression of data, particularly in a printer configuration, to achieve better compression ratios and processing speeds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If loss-less compression algorithms are used on image data, then compression is performed without quality loss, but compression ratios are poor (less than 2:1)
Solution Approach 1:
The patent segments image data into distinct color planes (e.g., cyan, magenta, yellow, black) and processes each plane independently through separate compression channels. This segmentation allows specialized compression techniques to be applied to each color plane, improving overall compression ratios while maintaining image quality through selective application of compression methods.
2Quantity of substance
If lossy compression algorithms are used on text data, then compression ratios improve, but visual artifacts and quality degradation occur
Solution Approach 1:
The patent applies different compression quality levels to different data types within the same image stream. Text regions undergo loss-less compression to preserve sharp edges and avoid artifacts, while photographic regions utilize lossy compression to achieve higher compression ratios. This local quality adaptation ensures optimal results for each region's specific requirements.
3Reliability
If mixed lossy and loss-less compression techniques are used, then both image and text data can be compressed effectively, but processing speed decreases and system complexity increases
Solution Approach 1:
The patent performs preliminary classification of image regions into text, photograph, and graphic areas before compression. By pre-identifying region types and preparing appropriate compression parameters in advance, the system avoids complex real-time decision-making during compression, thereby maintaining high processing speeds while applying the most effective compression method to each region.
Solution Approach 2:
The patent dynamically adjusts compression parameters and algorithm selection based on the detected content type in each image region. The system transitions between different compression modes (loss-less for text, lossy for photographs) according to the actual data characteristics, optimizing both compression effectiveness and processing efficiency for mixed-content images.
4Quantity of substance
If JPEG-type algorithms are used on scaled image data, then compression is achieved, but compression effectiveness is reduced compared to unscaled data
Solution Approach 1:
The patent changes the compression approach based on the resolution and scaling characteristics of the input data. For scaled or high-resolution data, the system adjusts compression parameters such as block size, sampling rates, and transformation methods to maintain effectiveness. This parameter adaptation allows JPEG-type algorithms to achieve good compression ratios even on scaled image data that would otherwise be difficult to compress.
Data Source
AI summary
One embodiment of the invention is directed to a printer that is configured to interleave color plane data. The interleaved data is compressed, thereby forming compressed data having runs, seedrow copies and literals. In the compression process, commands are buffered to enable independent and simultaneous operation of a run module, a seedrow copy module and a literal module used in forming the compressed data.