Cloud Streaming Server Region Detection and Adaptive Compression
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Solution Overview
Problem
Cloud streaming services based on video codecs are inefficient when dealing with static screens, as they capture and encode entire screens, leading to unnecessary data transmission and varying compression efficiency due to image type and technique used, causing service delays and performance issues across different set-top boxes.
Innovation Solution
A cloud streaming server that detects changed regions between frames and uses suitable still image compression techniques like PNG, paletted PNG, or JPEG based on region size and image type to encode and transmit only the changed areas, optimizing compression efficiency and service speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video codec is used for cloud streaming service, then motion sequences can be compressed effectively, but static screens are inefficient due to capturing and encoding entire screens
Solution Approach 1:
The patent divides the screen into multiple regions and identifies changed regions between frames. Instead of encoding the entire screen, only the changed regions are captured and transmitted. This segmentation approach eliminates unnecessary data transmission for static areas while maintaining effective compression for dynamic content.
2Productivity
If still image compression is applied to menu displays with slight changes, then compression efficiency improves, but detecting changed regions becomes more complex
Solution Approach 1:
The patent performs preliminary actions by capturing the entire screen first, then comparing consecutive frames to identify changed regions. This preliminary capture followed by differential analysis simplifies the detection process compared to attempting to directly identify changed regions without initial full-screen capture.
3Productivity
If adaptive compression technique is used for different image types, then compression efficiency varies significantly, but the complexity of identifying image types and selecting techniques increases
Solution Approach 1:
The patent changes parameters by applying different compression techniques (JPEG, PNG, GIF) based on the identified image type. The system analyzes image characteristics and selects appropriate compression parameters, achieving significant compression efficiency improvements while managing complexity through systematic parameter selection rather than complex adaptive algorithms.
4Reliability
If cloud streaming server processes all frames completely, then service quality is maintained, but service delays occur due to server load
Solution Approach 1:
The patent extracts only the changed regions from complete frames for processing and transmission. By taking out only the necessary portions (changed areas) rather than processing all frames completely, the system maintains service quality for dynamic content while significantly reducing server load and eliminating service delays.
5Productivity
If different compression formats are attempted and compared, then optimal compression is achieved, but the time required for format selection increases
Solution Approach 1:
The patent performs preliminary classification of image types before applying compression. By pre-categorizing images into types (photographs, graphics, etc.) and selecting the appropriate compression format in advance, the system achieves optimal compression ratios without the time-consuming process of attempting multiple formats and comparing results.
Data Source
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AI summary
The present invention relates to a system for a cloud streaming service, a method for a still image-based cloud streaming service and an apparatus therefor. The still image-based cloud streaming service can be provided by capturing the changed area in the changed frame by comparing same with the previous frame, selecting a still-image compression technique by considering any one or more from among the size of the changed area and image characteristics, and transmitting, to a user, the changed area encoded by the still-image compression technique. When providing a still image-based cloud streaming service, by utilizing still-image compression techniques which are appropriate to the conditions, the compression efficiency of the still image and speed of the cloud streaming service can be improved.