The proliferation of 5G/6G networks is fueling an explosion in rich media content, from 4K/8K streaming to immersive VR/AR and metaverse applications. Consumers and industries alike demand flawless visual experiences, making efficient, high-fidelity video compression a critical bottleneck. This technology directly addresses this by enabling superior subjective quality and data efficiency, positioning licensees to capitalize on the rapidly expanding global digital content market and meet escalating user expectations.
Significantly enhances subjective quality by dynamically adjusting color difference signal reproduction based on predicted luminance signal degradation, potentially improving viewer experience by 20%.
Achieves high-dimensional balance of compression efficiency and image quality by fully achromaticizing near-achromatic color difference signals, enabling up to 15% data reduction while maintaining visually consistent high-quality video.
Secures competitive advantage with a robust IP foundation, having passed rigorous examination against 7 prior art documents, ensuring a stable right with an exclusive period until 2040 for long-term business development.
This patent protects a video encoding and decoding system that enhances subjective quality for wide-gamut video by dynamically adjusting color difference signal reproduction based on predicted luminance degradation, and by fully achromaticizing near-achromatic color signals. It is a robust right, having successfully overcome a rejection notice, with clear claims and differentiation from prior art.
Adjacent white space includes advancements in adaptive bitrate streaming protocols, integration with AI-driven content analysis for dynamic compression, and hardware acceleration architectures optimized for this specific encoding method, where licensees could build further IP.
Assuming an enterprise streams 100TB of wide-gamut video monthly with a data transfer cost of $0.07/GB (AI est.), the annual transfer cost is estimated at ~$800K (AI est.). Applying the technology's 15% data reduction, a direct annual data transfer cost saving of ~$120K (AI est.) is expected. This is calculated as ~$800K (AI est.) total annual transfer cost × 15% reduction rate = ~$120K (AI est.) savings. Furthermore, maintaining high image quality could reduce user churn, potentially increasing annual revenue by several tens of millions of dollars.
X: Data Efficiency
Y: Subjective Image Quality