Market Context — Why This Technology, Why Now

The proliferation of 5G networks and edge computing is fueling an unprecedented surge in high-resolution video content consumption and real-time interactive applications. This creates immense pressure on existing network infrastructure and storage solutions. Companies are actively seeking advanced compression technologies to reduce bandwidth costs, optimize storage, and deliver superior user experiences to stay competitive. This patent offers a timely solution to these challenges, enabling businesses to meet escalating consumer expectations for immersive, high-quality digital content without prohibitive infrastructure investments.

Key Competitive Advantages
01

Enhances Image Quality with High-Precision Chrominance Prediction

02

Secures Market Advantage with High Uniqueness

03

Improves Data Compression Efficiency by 15%

Market Opportunity
Video Streaming & OTT Services
$65B–$100B globally (AI est.)
The video streaming services market, exemplified by platforms like Netflix and YouTube, continues to grow due to increasing demand for high-quality content. This technology directly contributes to reducing distribution costs and enhancing user experience.
Major streaming platforms Content delivery network providers Video codec developers Broadcast equipment manufacturers
VR/AR & Metaverse
$35B–$50B globally (AI est.)
Immersive experiences require high-resolution, low-latency video processing. This technology could enhance VR/AR device performance and content quality, driving market expansion.
VR/AR headset manufacturers Metaverse platform developers Immersive content creators Gaming console developers
Surveillance & Security
$20B–$30B globally (AI est.)
The advancement of smart cities and industrial IoT is accelerating the adoption of high-definition surveillance cameras. Efficient transmission and storage management of vast video data represent a critical application area for this technology.
Smart city solution providers Industrial IoT camera manufacturers Video management system developers Security system integrators
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects an intra-prediction device, decoding device, and program that enhance chrominance prediction accuracy by acquiring reference pixels from both surrounding and non-adjacent chrominance pixel lines under specific conditions, combined with luminance reference pixels. The claims are meticulously structured across five points, and the patent was granted after effectively addressing examiner objections, indicating high stability and low invalidation risk.

Competitive White Space

This patent primarily covers chrominance intra-prediction. White space exists in inter-prediction techniques, advanced motion compensation algorithms, or specialized hardware architectures for real-time video processing, allowing for complementary IP development.

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

For large-scale video streaming services, assuming an annual data transfer of 100PB and a data transfer/storage cost of ~$6.5K/PB (AI est.), annual operational costs could reach ~$650K (AI est.). Implementing this technology, with a 15% improvement in data compression efficiency, could result in an annual cost reduction of ~$650K × 15% = ~$100K (AI est.).

Speed to Market
6× faster than in-house development
This technology is based on an established intra-prediction algorithm designed to function as a module within video decoding devices. This facilitates easy integration into existing standard codec frameworks like HEVC and VVC, allowing rapid deployment as a software module without complex hardware modifications. Consequently, it significantly shortens time-to-market compared to developing similar technology in-house from scratch, enabling faster business expansion and monetization.
Competitive Positioning

X: Video Quality & Compression Efficiency
Y: Implementation Ease & Versatility

Business Models & Applications
🚀 Software Licensing
License software modules implementing this technology to video codec developers and device manufacturers. This could enhance product competitiveness by adding high-precision chrominance prediction capabilities.
💡 Cloud API Service
Offer this technology as a cloud-based video processing API. Video content providers and developers could easily utilize high-efficiency video compression and decoding services via the API, reducing development burden.
🔧 Embedded Solutions
Provide optimized solutions for embedded systems such as surveillance cameras, drones, and VR devices. This could achieve high-quality, high-efficiency video processing with limited resources.
Adjacent Application Opportunities
🎮 Gaming & Interactive Content
Real-time Rendering Optimization
In game engines and interactive content, optimizing chrominance component prediction for real-time generated video could reduce GPU load and memory usage while maintaining image quality. This is expected to enable richer graphic expressions on a wider range of devices.
⚕️ Medical & Remote Diagnostics
Efficient Transmission of High-Definition Medical Imaging
This technology could be repurposed for efficient transmission and storage of high-definition medical imaging data, such as MRI and CT scans, in telemedicine and surgical assistance. By minimizing image quality degradation while reducing data volume, it could lower network load and storage costs while maintaining diagnostic accuracy.
🚗 Autonomous Driving & In-Vehicle Cameras
In-Vehicle Sensor Data Compression
Applicable to systems that efficiently compress and process vast video data in real-time from numerous cameras and sensors in autonomous vehicles. This is expected to reduce the burden on in-vehicle computing resources, supporting faster and more accurate situational awareness and decision-making.
Integration Roadmap — Estimated 18-Month Deployment
Phase 1: Technical Feasibility Assessment & Design
Duration: 3 months
Assess the technology's compatibility with the adopting company's existing video processing systems, identifying necessary modifications and interfaces. Subsequently, conduct detailed design based on deployment requirements.
Phase 2: Prototype Development & Integration
Duration: 6 months
Develop a prototype to integrate the technology's algorithms into existing systems. Verify practical utility through functional integration, debugging, and basic performance benchmark tests.
Phase 3: Validation, Optimization & Production Deployment
Duration: 9 months
Conduct detailed validation experiments in a real-world environment, optimizing performance metrics such as compression efficiency, image quality, and processing speed. After final adjustments, initiate full production deployment and operation.
Technical Feasibility
This technology is designed as a module for integration into the intra-prediction unit of video decoding devices, and the patent claims state it can be integrated as a software update into existing standard codec frameworks like HEVC and VVC. This indicates high technical feasibility for low-cost deployment into existing video processing pipelines, without requiring extensive hardware changes or capital investment. The specific configurations for reference pixel acquisition and prediction parameter derivation units are clearly defined, establishing guidelines for software implementation.
Success Scenario
Implementing this technology could enable the delivery of higher-quality high-definition video over existing bandwidth. This is estimated to enhance user experience satisfaction, strengthen existing customer engagement, and contribute to new customer acquisition. Furthermore, it could reduce annual storage costs by up to 15%, optimizing operational costs and improving business competitiveness.
Patent Record
APPLICATION NO.
JP2021-200884
REGISTRATION NO.
7768746
FILING DATE
2021/12/10
GRANT DATE
2025/11/04
EXPIRATION DATE
2041/12/10
PATENT HOLDER
日本放送協会
Examination History
2024-11-11
Request for Examination
2025-07-22
Office Action
2025-09-22
Applicant's Response
2025-09-22
Amendment (Voluntary)
2025-10-07
Decision to Grant