Screen Data Encoding via Content Attribute Segmentation
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Solution Overview
Problem
In virtual desktop infrastructure (VDI) environments, existing methods for transmitting screen data are inefficient due to high transmission costs and low accuracy, as they uniformly process data without considering the varying attributes of content.
Innovation Solution
A method and apparatus where a cloud server determines the attributes of screen data content, encodes it using a suitable method that prioritizes data loss reduction over speed, and transmits the encoded data along with attribute information, allowing for classification and tailored encoding for each group of content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If screen data is encoded using conventional uniform encoding methods, then transmission speed is maintained, but transmission costs increase and accuracy decreases
Solution Approach 1:
The patent segments screen data into multiple regions based on content attributes (text, image, video, mixed content) and applies different encoding methods to each region. This segmentation allows the system to optimize encoding for each content type independently, reducing overall transmission costs while maintaining accuracy.
Solution Approach 2:
The patent implements local quality by determining content attributes for different regions of the screen and applying encoding methods tailored to each region's specific content type. Text-heavy regions use text-optimized encoding, image regions use image-optimized encoding, and mixed regions use adaptive encoding, thereby reducing transmission costs without compromising overall accuracy.
2Manufacturing precision
If screen data is encoded with focus on data loss reduction, then accuracy improves, but encoding speed decreases
Solution Approach 1:
The patent divides screen data into multiple content regions and applies different encoding priorities to each region. Text regions use encoding methods prioritizing accuracy, while image regions use methods balancing speed and quality. This segmentation allows the system to achieve high overall accuracy without uniformly sacrificing encoding speed across all content types.
Solution Approach 2:
The patent changes encoding parameters dynamically based on content attributes. For text content, encoding parameters are adjusted to maximize accuracy; for image content, parameters are adjusted to balance speed and quality. This parameter adaptation allows the system to achieve high accuracy where needed while maintaining encoding speed for other content types.
3Loss of energy
If uniform encoding method is applied to all screen data, then processing simplicity is maintained, but transmission costs increase
Solution Approach 1:
The patent automatically segments screen data into content-based regions and applies appropriate encoding methods to each segment. This automated segmentation and selective encoding reduces transmission costs by optimizing each region's encoding approach, while the automation maintains operational simplicity without requiring manual intervention.
4Manufacturing precision
If content attributes are analyzed and classified, then encoding accuracy improves, but processing complexity increases
Solution Approach 1:
The patent segments screen data into content regions and determines attributes for each segment independently. This segmentation approach improves encoding accuracy by tailoring encoding to each region's content type, while the modular attribute determination process manages processing complexity through systematic, region-by-region analysis.
Solution Approach 2:
The patent determines content attributes (text, image, video, mixed) for different regions and changes encoding parameters accordingly. This parameter adaptation based on attribute analysis improves encoding accuracy, while the automated attribute determination and parameter selection processes manage system complexity through algorithmic decision-making.
Data Source
AI summary
The exemplary embodiments relate to providing screen data to a client, through a cloud server, and displaying the screen data in the client. The cloud server may encode the screen data in an encoding method that is independently determined according to attributes of each of a plurality of contents which form the screen data, and the client may decode the received screen data based on the encoding method in the cloud server and may display the decoded screen data. The screen data may be efficiently provided by performing encoding based on attributes of respective contents which form the screen data, compared to a case where only one encoding method is used.