Remote Display Tiling With Hybrid Text and Image Compression
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Solution Overview
Problem
Current remote computing technologies face bottlenecks in encoding and transmitting display data due to the increasing amount of image and video data, which requires high CPU overhead and is not efficient for mixed data types like text and images, especially over slower networks.
Innovation Solution
A method and system that divide the remote computer display data into tiles, apply a color reduction algorithm to determine if each tile represents image or text data, and use lossy compression for image data and lossless compression for text data, transmitting a hybrid of JPEG and ZRLE encoded data to reduce CPU overhead and optimize data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If high compression encoding (e.g., RLE) is used to reduce data transmission volume, then data transmission efficiency is improved, but CPU overhead increases
Solution Approach 1:
The display screen is divided into multiple tiles, and each tile is independently encoded. This segmentation allows the system to apply different encoding strategies to different regions, reducing the overall CPU overhead while maintaining compression efficiency for the entire display data
Solution Approach 2:
Different encoding methods are applied to different tiles based on their content characteristics. Tiles containing text or simple graphics use lossless compression, while tiles with complex images use lossy compression. This local differentiation optimizes the balance between compression ratio and CPU overhead for each region
2Manufacturing precision
If lossless compression is used to maintain exact display representation, then display accuracy is improved, but data transmission volume increases
Solution Approach 1:
The system applies different encoding precision to different regions: lossless compression for text and simple graphics where accuracy is critical, and lossy compression for image regions where some quality degradation is acceptable. This resolves the contradiction by making precision local rather than universal
3Productivity
If encoding algorithms are made more complex to handle mixed data types, then encoding efficiency is improved, but device complexity increases
Solution Approach 1:
The display is segmented into tiles that are independently encoded, allowing simple per-tile encoding operations rather than complex global encoding. This segmentation reduces algorithmic complexity while maintaining overall encoding efficiency
Solution Approach 2:
The system changes encoding parameters (lossless vs. lossy compression) based on tile content characteristics rather than using a single complex algorithm for all content. This parameter-based approach simplifies the overall system while adapting to different data types
Data Source
AI summary
A remote computer having a processor and a display, said remote computer being connected via a network to a local computer having a processor and a display, wherein the processor of the remote computer is configured to divide at least part of the remote computer display into a grid having a plurality of tiles, determine whether each tile represents image data or text data, encode each tile representing text data using a lossless compression, encode each tile representing image data using a lossy compression, and transmit display data comprising said lossy encoded image data and said lossless encoded text data from said remote computer to said local computer, whereby a user is able to view said remote computer display on said local computer display.