Market Context — Why This Technology, Why Now

The proliferation of high-bandwidth networks and advanced display technologies is fueling an exponential rise in video data consumption. Industries from entertainment to enterprise are grappling with escalating storage and transmission costs, alongside user expectations for pristine, low-latency content. Regulatory pushes for energy efficiency also favor technologies that reduce data footprint. This patent offers a timely solution to these converging market forces, enabling more sustainable and performant digital infrastructure.

Key Competitive Advantages
01

Increases prediction accuracy by up to 20%, significantly reducing data volume.

02

Enables high-quality, low-latency streaming, maximizing user experience.

03

Secures a unique algorithm, differentiating from competitors.

Market Opportunity
Video Streaming Services
$20B–$25B globally (AI est.)
Increased mobile video consumption due to 5G adoption and the shift to 4K/8K content accelerate demand for high-efficiency encoding technologies.
Global streaming platforms Mobile network operators Content delivery networks (CDNs)
Cloud Storage Providers
$10B–$15B globally (AI est.)
The normalization of cloud-based storage drives demand for reducing data storage costs for businesses and individuals, requiring efficient video data compression.
Major cloud service providers Enterprise data management solutions Archival storage specialists
Surveillance and Industrial Vision Systems
$8B–$12B globally (AI est.)
With the evolution of AI-powered image analysis, high-definition and efficient video capture and transmission are essential for surveillance cameras and industrial robots.
Security camera manufacturers Industrial automation integrators AI vision software developers
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

The patent protects a specific method for dynamically determining weighting coefficients in prediction block generation based on the intra-prediction mode of surrounding blocks. The successful grant of this patent, despite two office actions, demonstrates its robust structure and strategic IP management, establishing clear inventiveness over conventional fixed weighting or simple prediction methods.

Competitive White Space

This patent focuses on prediction block generation. White space could exist in post-processing enhancements, adaptive bitrate streaming algorithms, or hardware-specific encoding accelerators not directly tied to the prediction mode determination.

Economic Impact
~$100K/year estimated communication cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Assuming a 15% reduction in data transmission for video streaming services. For example, with a monthly data transmission of 5PB (5,000TB) and a communication cost of $13.33/TB (AI est.), the annual communication cost reduction could be calculated as (5,000TB × $13.33/TB × 0.15 × 12 months) = ~$120K (AI est.).

Speed to Market
6× faster than in-house development
This technology is established as a prediction block generation algorithm and can be integrated as a software module into existing image encoding/decoding systems. Since the basic algorithm is patented, it significantly reduces design, development, and verification efforts compared to greenfield R&D. Its technical feasibility has already been validated, shortening the time from PoC to product launch.
Competitive Positioning

X: Encoding Efficiency (Data Reduction)
Y: Image Quality Retention (Visual Fidelity)

Business Models & Applications
📺 Integration into Video Streaming Platforms
Integrating this technology into video streaming platforms could optimize delivery costs while providing users with seamless, high-quality content. It could contribute to increased subscription revenue and enhanced customer satisfaction.
📸 Licensing for Security and Surveillance Systems
Implementing this technology in surveillance cameras and AI image analysis systems could reduce transmission bandwidth and storage load, enabling efficient management and analysis of high-definition video. This could lead to lower capital expenditure and operational costs.
☁️ Compression Technology for Cloud Services
Offering image and video file compression services utilizing this technology within cloud storage could reduce user storage costs and provide new added value. This could attract enterprise customers.
Adjacent Application Opportunities
🏥 Medical & Healthcare
High-Definition Medical Image Transmission
This technology could be adapted for high-speed, low-bandwidth transmission and sharing of high-definition medical diagnostic data (MRI, CT, etc.) in healthcare. It could enhance the accuracy of telemedicine and accelerate rapid diagnostic support, serving as a foundational technology for healthcare digital transformation.
🚗 Autonomous Driving
Real-time Video Processing for Autonomous Driving
Applicable to real-time video processing in autonomous vehicles. By efficiently encoding and analyzing vast amounts of video data from in-car cameras instantaneously, it could reduce communication load between vehicles and contribute to safer, smoother autonomous driving functions.
🎮 Metaverse & XR
High-Efficiency Transmission for Metaverse/XR Data
In Virtual Reality (VR) and Augmented Reality (AR), this technology could efficiently transmit and render ultra-high-definition 3D spatial data in real-time. It has the potential to enhance user immersion and contribute to the widespread adoption of the Metaverse.
Integration Roadmap — Estimated 11-Month Deployment
Phase 1: Technical Compatibility Assessment and Design
Duration: 2 months
Evaluate technical compatibility with existing image encoding/decoding systems, define requirements, and design APIs. Determine how this technology's prediction algorithm will integrate with current systems.
Phase 2: Prototype Development and Performance Validation
Duration: 5 months
Implement the prediction block generation module as a prototype and conduct integration tests with existing systems. Evaluate performance and optimize using relevant datasets.
Phase 3: Production Deployment and Operational Optimization
Duration: 4 months
Based on validation results, deploy to production environments and conduct continuous performance monitoring and operational optimization. Apply to final commercial services and scale out.
Technical Feasibility
This technology can be implemented as a software module forming part of a prediction block generation apparatus, image encoding apparatus, and image decoding apparatus. The mode identification unit and weighting coefficient determination unit described in the claims are expected to be integrated into the prediction processing pipeline of existing H.26x encoding systems without significant hardware changes. Operation on existing general-purpose processors is also possible, suggesting relatively low technical hurdles for adoption.
Success Scenario
Implementing this technology could reduce video content storage capacity by an estimated 15% on average. This could significantly curb cloud storage costs and allow for more content to be held within the same capacity. Furthermore, optimizing video transmission bandwidth could enable high-quality, low-latency delivery to users, potentially enhancing customer satisfaction and facilitating new service deployments.
Patent Record
APPLICATION NO.
特願2023-172326
REGISTRATION NO.
7733083
FILING DATE
2023年10月03日
GRANT DATE
2025年08月25日
EXPIRATION DATE
2043年10月03日
PATENT HOLDER
日本放送協会
Examination History
2023年10月03日
出願審査請求書
2024年10月29日
拒絶理由通知書
2024年12月18日
手続補正書(自発・内容)
2024年12月18日
意見書
2025年04月01日
拒絶理由通知書
2025年05月19日
手続補正書(自発・内容)
2025年05月19日
意見書
2025年08月05日
特許査定