The global shift towards ubiquitous video consumption on mobile and IoT devices, coupled with the proliferation of high-resolution formats like 4K/8K, intensifies the need for efficient, quality-preserving video processing. Regulatory pressures for sustainable data usage and competitive dynamics demanding flawless user experiences drive the adoption of technologies that optimize bandwidth without compromising visual fidelity. This patent offers a critical solution to these challenges, enabling broader market reach and superior service delivery.
Maintain High Image Quality for Low Bit-Depth Video: Optimally controls filter strength based on input bit depth, suppressing unintended pixel value corrections and maintaining high-definition quality even in low bit-depth video.
Enhance Video Processing Efficiency and Reduce Costs: Reduces unnecessary computations through deblocking filter processing tailored to video signal characteristics, improving processing efficiency, reducing system load, and contributing to operational cost savings.
Secure IP Foundation for Business Operations: Establishes patentability through a standard examination process, contributing to stable operation across various video environments. Licensees can confidently utilize this technology.
This patent protects a deblocking filter control device and program that optimally adjusts filter strength based on the input video signal's bit depth, particularly through a unique offset addition and bit-shift conversion logic for low bit-depth inputs. The claims are robust, having withstood two office actions and rigorous examination, ensuring a strong and defensible IP position.
This patent primarily covers adaptive deblocking filter control. White space exists in developing novel content-aware encoding algorithms that integrate this technology, or in hardware-accelerated implementations for real-time, ultra-low latency applications.
Inadequate deblocking filter processing leads to video quality degradation, re-encoding, and data correction. Assuming a licensee produces/distributes 1,000 hours of video content annually, with 20% potentially experiencing quality degradation, and re-processing costs (including labor and computing resources) at ~$650/hour (AI est.). This technology could reduce these re-processing costs by 50%. Calculation: 1,000 hours/year × 20% × ~$650/hour (AI est.) × 50% = ~$65K/year (AI est.) in direct cost savings. Additionally, maintaining high image quality could generate over ~$150K/year (AI est.) in revenue opportunities through improved customer engagement.
X: Video Quality Retention Efficiency
Y: Implementation & Operational Cost Performance