Video Noise Reduction Using Spatial-Temporal Patch Correlation

The patent divides the image processing task into multiple passes: a first pass processes pixels using spatial information from the current frame, while a second pass uses temporal information from previous frames. This segmentation allows complex noise reduction to be broken into manageable steps that can be optimized for speed.

The patent performs preliminary noise reduction in the first pass using only spatial information before proceeding to the second pass with temporal information. This preliminary action reduces the overall noise level early, making subsequent processing more efficient and effective.

The patent applies different processing strategies to different regions of the image based on local characteristics. By analyzing pixel patches and their similarities, the method adapts the noise reduction strength locally, preserving edges in regions where they exist while aggressively reducing noise in homogeneous areas.

The patent uses dynamic thresholding and adaptive weighting in the averaging process. The similarity thresholds and weights applied to different pixel patches are adjusted dynamically based on local image characteristics, allowing the algorithm to preserve sharp edges while reducing noise in smoother regions.

The patent introduces camera directional data (from gyroscopes or accelerometers) as an intermediary to bridge the gap between actual camera movement and image frame alignment. This external sensor data serves as a mediator that simplifies the complexity of tracking and compensating for camera movements without requiring complex image analysis.

The patent replaces complex mechanical image stabilization systems with computational methods that use sensor data to guide the noise reduction process. Instead of physically stabilizing the camera mechanism, the system uses digital processing guided by inertial sensor measurements to achieve similar effects.

The patent segments the computational task into two distinct passes: spatial processing in the first pass and temporal processing in the second pass. This segmentation allows the system to manage computational energy by breaking down the complex task of combining spatial and temporal data into smaller, more energy-efficient steps.

The patent performs preliminary spatial noise reduction before applying temporal filtering. This preliminary action reduces the overall noise level and simplifies the subsequent temporal processing, reducing the computational energy required for the combined spatial-temporal analysis.