Market Context — Why This Technology, Why Now

Global demand for high-quality, low-latency video is surging across all sectors, from entertainment to enterprise. As data volumes continue to grow exponentially, efficient video compression is no longer a luxury but a necessity for managing infrastructure costs, improving user experience, and enabling new applications like immersive VR/AR and edge AI. This technology offers a timely solution to these pressures, providing a competitive edge in a rapidly expanding market.

Key Competitive Advantages
01

Reduces video data volume by ~15% while maintaining high image quality compared to existing technologies, through intra-prediction mode based synthesis region determination and weighted averaging.

02

Optimized for real-time processing, offering an advantage for high-definition live streaming and low-latency VR/AR content in 5G environments due to its design that avoids increasing encoder-side computation time.

03

Provides a stable intellectual property foundation, having cleared examiner objections through detailed argumentation against 6 prior art documents, ensuring strong patent validity and business development stability.

Market Opportunity
📺 Video Streaming & Broadcast
$8B globally (AI est.)
The proliferation of 4K/8K content and the expansion of subscription models continuously increase demand for high-quality, low-latency video streaming.
Major streaming service providers Broadcast and media companies Content delivery network (CDN) operators
☁️ Cloud & Data Centers
$33.5B globally (AI est.)
Efficient compression technology directly reduces operational costs and improves service quality, addressing challenges associated with storing and transferring large volumes of video data.
Cloud service providers (CSPs) Data center infrastructure companies Enterprise IT solutions providers
🎮 VR/AR & Metaverse
$13.5B globally (AI est.)
Low-latency and highly efficient video codecs are essential for processing and delivering high-definition 3D imagery in real-time for VR/AR and metaverse applications.
VR/AR headset manufacturers Metaverse platform developers Immersive content creators
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a decoding apparatus's method for generating prediction images, specifically covering the determination of synthesis regions, the application of different prediction processes, and the logic for determining weights in weighted averaging. The patent's validity is strong, having successfully overcome examiner objections during prosecution, demonstrating clear novelty and inventiveness over prior art.

Competitive White Space

This patent primarily covers decoding algorithms. Licensees could explore building additional IP around encoding-side optimizations, adaptive streaming protocols, or hardware acceleration architectures not explicitly claimed here, to create a broader solution suite.

Economic Impact
~$1.5M/year estimated storage and bandwidth cost reduction per facility (AI est.).
estimated ROI · USD · AI analysis
ROI Calculation Logic

Assuming a licensee operates a video streaming service, storing and distributing 100PB of video data annually. Applying the 15% data reduction effect from this technology, savings are expected in both storage costs (e.g., ~$3,333/PB/month (AI est.)) and bandwidth costs (e.g., ~$133/TB/month (AI est.)). Specifically, (100PB × 0.15 × $3,333/PB × 12 months) + (100PB × 0.15 × $133/TB × 1000TB/PB × 12 months) = an estimated annual cost reduction of ~$1.5M (AI est.).

Speed to Market
5× faster than in-house development
This technology significantly shortens the foundational research and algorithm development phases, as the algorithm for improving prediction accuracy and encoding efficiency in video decoding is already established and patented. Designed for integration into existing video processing pipelines and software frameworks, licensees could potentially reduce market entry time by approximately 3.2 years compared to in-house development, enabling faster business deployment and monetization.
Competitive Positioning

X: Cost Efficiency
Y: Video Quality & Data Efficiency

Business Models & Applications
📄 Licensing Model
Licensees can integrate this technology into existing products or services, paying royalties based on usage to enhance product competitiveness and expand market share.
🤝 Joint Development & Service Provision Model
Jointly develop optimized video compression and distribution solutions for specific industries, leveraging this technology as a core, and offer them as SaaS to secure recurring revenue.
💡 Chipset Integration Model
Optimize this technology for hardware (e.g., SoCs) and provide it to camera module or edge AI device manufacturers, enabling high-efficiency video processing at the device level and creating new added value.
Adjacent Application Opportunities
🎥 Surveillance & Security
Ultra-HD Surveillance Camera Systems
Applying this technology to surveillance camera systems could enable long-duration recording and storage of 4K/8K high-definition video at lower bitrates. This could reduce cloud storage costs while improving the accuracy of AI-based anomaly detection, leading to more efficient security operations.
🚗 Autonomous Driving & In-Car Cameras
Real-time Video Processing for Automotive AI
This technology could enable high-efficiency processing and transmission of vast video data from autonomous vehicle cameras with reduced computational load. This could contribute to improving real-time recognition accuracy for edge AI and alleviating data upload burdens to the cloud, enhancing safety and reliability for next-generation mobility.
telehealth/遠隔医療
High-Quality, Low-Latency Tele-diagnosis
In telehealth, this technology could reduce data volume while maintaining image quality for real-time transmission of high-definition medical images and videos. This could enable precise remote diagnostics in stable communication environments, helping to bridge healthcare disparities.
Integration Roadmap — Estimated 12-Month Deployment
Technical Evaluation & Prototype
Duration: 3 months
Integrate the core algorithm into existing video processing pipelines, evaluate performance on target devices and service environments, and develop an initial prototype.
Implementation & Optimization
Duration: 6 months
Based on prototype results, optimize and implement the algorithm for specific applications, establish integration with existing systems, and conduct functional and performance benchmarks.
Validation & Market Preparation
Duration: 3 months
Verify effectiveness through small-scale proof-of-concept (PoC) experiments in real environments, incorporate feedback, and finalize adjustments for productization and market entry strategy.
Technical Feasibility
This technology focuses on improving prediction algorithms in video decoding. Functions such as the synthesis region determination unit and prediction image synthesis unit, as described in the claims, are presumed to be implementable as feature additions or algorithm updates to existing software decoder modules. It is expected to operate in general-purpose CPU/GPU environments and possesses technical compatibility for relatively easy integration into existing video processing infrastructure without requiring extensive hardware changes or new capital investment.
Success Scenario
Upon adopting this technology, a licensee's video streaming platform could potentially deliver the same quality video with an average of 15% less data. This could significantly reduce CDN costs and is estimated to shorten user buffering times by up to 20%. Consequently, it could simultaneously enhance customer satisfaction and optimize operational costs, establishing a competitive advantage in the market.
Patent Record
APPLICATION NO.
特願2023-141326
REGISTRATION NO.
7597880
FILING DATE
2023/08/31
GRANT DATE
2024/12/02
EXPIRATION DATE
2043/08/31
PATENT HOLDER
日本放送協会
Examination History
2023年08月31日
出願審査請求書
2024年09月03日
拒絶理由通知書
2024年10月16日
手続補正書（自発・内容）
2024年10月16日
意見書
2024年10月29日
特許査定