Video Decoder QP Prediction for Neural Network Block Filtering

The QP prediction model performs preliminary prediction of the second QP based on previously decoded information (such as QP values from neighboring blocks or previous frames) before the actual filtering operation. This preliminary action enables more accurate QP determination without requiring complex real-time calculations during the filtering process, thus improving measurement precision while controlling device complexity.

The patent introduces an intermediary QP prediction model that acts as a mediator between the available decoded information and the required QP value for filtering. This intermediary component processes the relationship between historical QP data and current block characteristics to generate an accurate prediction, avoiding the need for complex direct calculation methods while maintaining high precision in QP determination.

The patent implements dynamic QP adjustment by allowing the QP value to vary across different blocks and regions based on local characteristics such as texture complexity, motion activity, and edge presence. This dynamic approach enables the system to use a wider range of QP values (improving filtering effect) while adapting to local conditions to minimize information loss in important regions. The QP is no longer a fixed global parameter but a dynamic local parameter that optimizes the balance between compression and quality.

Different QP values are applied to different regions of the video data based on local characteristics. Regions with important visual information (edges, textures, motion) receive smaller QP values (less quantization, less information loss), while regions with less important information receive larger QP values (more compression). This local quality approach allows the system to expand the effective QP range for optimization while minimizing overall information loss by protecting critical visual elements.