Printer Image Layer Merging with Dynamic Resource Estimation
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Solution Overview
Problem
Existing methods for processing complex page description language (PDL) input in printers with limited memory resources face challenges such as high computational complexity, high memory storage requirements, degraded output quality, and potential out-of-resources conditions, particularly when handling unusual cases with overlapping translucent objects.
Innovation Solution
A method that estimates resources required to combine image layers using a first and second combining operation, selecting between merging and flattening operations based on resource availability, to generate a combined layer efficiently and effectively manage memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If bitmap compression is used to reduce memory storage requirements, then memory usage is reduced, but processing performance decreases due to decompression requirements and output quality degrades due to compression artifacts
Solution Approach 1:
The patent uses lossless fillmap compression that allows the compressed data to be discarded after processing, eliminating the need for long-term storage of high-quality uncompressed bitmaps. The fillmap format enables compact representation that can be decompressed on-demand without quality loss, making the compression artifacts issue irrelevant while maintaining performance.
2Quantity of substance
If fillmap merging is used to reduce memory usage, then memory resources are saved, but the system may exhaust resources when handling unusual cases with overlapping translucent objects
Solution Approach 1:
The patent implements a feedback mechanism that monitors memory usage during the fillmap merging process. When resource thresholds are approached, the system dynamically adjusts its behavior by switching to alternative processing strategies, such as processing objects in smaller batches or using different compositing approaches, thereby preventing resource exhaustion while maintaining reliability.
Solution Approach 2:
The system dynamically adapts its processing strategy based on the complexity of the PDL input and available memory resources. For unusual cases with many overlapping translucent objects, the system can switch between different merging approaches or process objects in staged batches, making the memory management flexible rather than static.
3Quantity of substance
If PDL input is divided into batches for processing, then memory requirements are reduced, but processing complexity increases and output quality may degrade
Solution Approach 1:
The patent segments the PDL processing into distinct phases: parsing, scan conversion to fillmaps, merging, and final rendering. Each phase operates with controlled memory usage, processing objects in manageable batches while maintaining the ability to handle complex compositing scenarios. The fillmap format enables efficient batch processing without sacrificing the ability to represent complex graphical objects.
Data Source
AI summary
A method for combining layers of an image represented using an intermediate format receives at least two layers from the plurality of layers to be combined and estimates resources required to combine the received layers using a first combining operation. The first combining operation comprises at least rasterizing data of the received layers. The method attempts to combine the received layers using a second combining operation to produce an output in the intermediate format. In response, the method generates a combined layer for the image by combining the received layers in accordance with a selected one of the first combining operation (merge & flatten) and the second combining operation (merge). The selected combining operation is based on success of the attempt. Desirably the method is performed within a printer apparatus where limited memory and/or computing resources are available for image rendering which could otherwise limit the rendering of complex pages.