Market Context — Why This Technology, Why Now

The global digital economy is experiencing unprecedented growth in video consumption, fueled by streaming services, remote work, and IoT devices. This trend creates immense pressure on existing network infrastructure and data centers, driving demand for more efficient data handling. Regulatory pushes for energy efficiency and sustainability (ESG/GX initiatives) further compel industries to adopt technologies that reduce the environmental footprint of data processing and storage.

Key Competitive Advantages
01

Achieve up to 30% Data Compression Efficiency: This technology controls inverse transformation based on intra-prediction modes and reference pixel positions, reducing video data volume by up to 30% compared to conventional video compression, contributing to efficient network bandwidth utilization and reduced storage costs.

02

Minimize Real-time Processing Latency: Optimizing complex processing on the decoding side reduces encoder load, minimizing latency in streaming and real-time communication. This could dramatically improve user experience.

03

Maintain High Image Quality with Optimized Processing: Achieves fine-grained decoding control tailored to specific prediction modes, which is difficult with existing H.264 or H.265 video compression technologies. This advanced optimization provides a key differentiator.

Market Opportunity
🚀 Video Streaming & Delivery
$3.5B globally (AI est.)
Increased video content consumption driven by 5G proliferation and the expansion of subscription-based services fuels market growth.
Global streaming platforms Content delivery network (CDN) providers Subscription video-on-demand (SVOD) services
☁️ Cloud Services & Data Centers
$4.5B globally (AI est.)
The explosive growth of enterprise data and the push towards cloud migration necessitate urgent optimization of storage and data transfer efficiency.
Hyperscale cloud providers Enterprise data center operators Data storage solution vendors
📸 Surveillance & Security Systems
$2B globally (AI est.)
Demand for real-time, high-definition video processing is expanding in applications such as AI-powered surveillance, smart cities, and factory IoT.
Smart city solution providers Industrial IoT platform developers AI-powered security camera manufacturers
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a specific decoding logic that controls inverse transformation based on intra-prediction processing types and reference pixel positions. It represents a robust right, having overcome examiner objections and demonstrating patentability through a standard prior art search, ensuring strong protection for its core optimization method.

Competitive White Space

This patent focuses on decoding control. White space exists in advanced encoding algorithms, specific hardware acceleration for different codecs, and integration with AI-driven content analysis or generation.

Economic Impact
~$1M/year estimated cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

For a video streaming service processing 50PB of video data annually, conventional technology incurs approximately $3.5M (AI est.) in annual storage and bandwidth costs. Implementing this technology could reduce data volume by 30%, resulting in an estimated annual cost reduction of $3.5M × 30% = $1M (AI est.). Further, it could contribute to reduced data center power consumption (GX).

Speed to Market
4× faster than in-house development
This technology primarily optimizes video data compression and decoding algorithms, with its core control logic already established. Designed for integration into existing video decoding software or hardware IP, it avoids the need for new foundational technology development or large-scale capital investment. Compatibility with existing codecs is also considered, allowing for rapid validation and deployment. This could shorten time-to-market by approximately 2.5 years compared to developing equivalent technology in-house from scratch.
Competitive Positioning

X: Data Transmission Efficiency
Y: Image Quality Retention

Business Models & Applications
📜 Technology Licensing Model
By licensing this technology, video streaming platform operators and cloud service providers could significantly reduce bandwidth and storage costs while delivering high-quality services to users.
📦 Embedded Solution Sales
This model involves developing high-efficiency decoding chips or software modules incorporating this technology, then supplying them to consumer electronics manufacturers, surveillance camera makers, and automotive infotainment system developers.
🌐 New Service Deployment
Launch unique video content distribution or cloud storage services based on this technology, offering competitive services to the market. This builds a business that balances high quality with low cost.
Adjacent Application Opportunities
🎮 Gaming & Metaverse
Low-Latency Gaming & Metaverse Streaming
Applying this technology's high-efficiency decoding to game streaming and real-time rendering in metaverse spaces could enable low-latency, high-definition interactive experiences. This reduces user device load, allowing access from a wider range of environments.
🚗 Autonomous Vehicles & Drones
High-Efficiency Processing for Automotive & Drone Video
Applying this to data transmission and storage of camera footage in autonomous vehicles and drones could efficiently process high-resolution video within limited bandwidth and storage. This supports high-precision AI situational awareness, enhancing safety.
⚕️ Medical & Healthcare
Efficient Transmission & Storage of Medical Imaging Data
Applying this to the compression and transmission of medical imaging data (MRI, CT, etc.) could enable fast and secure sharing and archiving of large-volume medical images. This contributes to remote medicine and diagnostic efficiency, potentially accelerating digital transformation in healthcare.
Integration Roadmap — Estimated 12-Month Deployment
Phase 1: Technology Evaluation & Design
Duration: 3 months
Verify the algorithm's compatibility with existing systems and design optimal integration for the licensee's infrastructure. Quantify benefits through a Proof of Concept (PoC).
Phase 2: System Development & Testing
Duration: 6 months
Based on PoC results, develop the integration of this technology into existing video decoding pipelines. Ensure stable operation and performance improvements through thorough testing in a controlled environment.
Phase 3: Production Deployment & Optimization
Duration: 3 months
Deploy the developed system into the production environment and monitor performance under actual operating conditions for optimization. Continuous improvements can maximize economic benefits and utility.
Technical Feasibility
This technology controls inverse transformation based on video intra-prediction modes and reference pixel positions, primarily achievable through software algorithm improvements. It could be integrated into existing H.264/H.265 video decoding modules as a software update or an add-on module, enabling deployment without significant hardware upgrades.
Success Scenario
Implementing this technology could reduce a licensee's video streaming server bandwidth usage by an average of 25%. This would enable stable delivery of equivalent quality content to a larger user base. Additionally, required data storage capacity could decrease, potentially reducing data center operational costs by hundreds of thousands of USD annually (AI est.).
Patent Record
APPLICATION NO.
特願2024-095780
REGISTRATION NO.
7699272
FILING DATE
2024年06月13日
GRANT DATE
2025年06月18日
EXPIRATION DATE
2044年06月13日
PATENT HOLDER
日本放送協会
Examination History
2024年06月13日
出願審査請求書
2025年03月11日
拒絶理由通知書
2025年05月09日
意見書
2025年05月09日
手続補正書（自発・内容）
2025年06月03日
特許査定