Content-Aware Moving Image Compression for Low-Latency Streaming
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Solution Overview
Problem
Existing technologies experience delays in image display on client terminals due to communication latency between the client and server, leading to degraded realism and potential motion sickness, especially with high image quality requirements.
Innovation Solution
An image data transfer apparatus and method that includes a drawing section, a communication status acquisition section, a compression coding section, and a communication section to adjust data size based on communication status, enabling efficient streaming and compression of moving images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image data is transmitted via network communication to achieve real-time display, then image quality can be improved through streaming from a server, but delay time period increases due to communication latency
Solution Approach 1:
The image data is divided into multiple blocks that can be independently compressed and transmitted. This segmentation allows the system to prioritize and transmit critical image blocks first, reducing the overall delay time while maintaining image quality through selective transmission of essential data portions.
Solution Approach 2:
The system performs preliminary compression coding on image data blocks before transmission, and uses prediction techniques to estimate future image states. This preliminary processing reduces the amount of data that needs to be transmitted in real-time, thereby reducing communication delay while preserving image quality.
2Manufacturing precision
If communication data rate is increased to improve image quality, then image quality improves, but communication bandwidth consumption increases
Solution Approach 1:
The system applies different compression rates to different image blocks based on their importance and characteristics. Critical regions receive higher quality compression while less important regions use lower compression rates. This local differentiation maintains overall image quality while significantly reducing total bandwidth consumption compared to uniform high-quality transmission.
Solution Approach 2:
The system dynamically adjusts compression parameters based on communication conditions and image content. By changing compression ratios, block sizes, and transmission priorities according to real-time requirements, the system optimizes the balance between image quality and bandwidth usage, achieving high quality where needed without wasting bandwidth on less critical data.
Data Source
AI summary
An image contents acquisition section in a compression coding section of a server acquires information associated with contents indicated by a moving image generated by an image generation section. A communication status acquisition section acquires a status of communication with an image processing apparatus corresponding to a data transmission destination. A compression coding processing section adjusts a data size of the moving image according to a change of the communication status, by using means determined on the basis of the contents indicated by the moving image, and compression-codes data of the moving image. A communication section transmits compression-coded data to the image processing apparatus.