Video Noise Filtering via Motion-Compensated Block Weighting
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Solution Overview
Problem
Video data is often corrupted by noise during capture, processing, and presentation, which adversely affects subsequent processing stages and degrades the quality of the video data.
Innovation Solution
A method and system for filtering noise from video data by identifying and selecting pixel blocks based on cost values indicative of correlation, assigning weights, and generating filtered pixels through block matching motion estimation and weighted averaging, utilizing both filtered and unfiltered reference pictures to maintain image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If noise filtering is applied to video data, then image quality is improved, but image details may be lost or blurred
Solution Approach 1:
The patent applies different filtering strategies to different regions of the image based on local characteristics. Motion-compensated filtering is applied to stationary regions while preserving details in moving regions, achieving local optimization of noise reduction without uniform blurring across the entire image.
Solution Approach 2:
The patent performs motion estimation and compensation before noise filtering. By predicting motion vectors and compensating for motion in advance, the filtering process can distinguish between actual motion and noise, preventing loss of important image details while removing noise.
2Reliability
If traditional noise filtering methods are used, then noise is removed, but processing complexity increases
Solution Approach 1:
The patent divides the image into multiple blocks and processes each block independently with motion estimation and filtering. This segmentation approach reduces overall processing complexity by allowing parallel processing and avoiding the need to analyze the entire image as a single unit.
Solution Approach 2:
The patent uses motion compensation to create predicted blocks from reference frames, copying relevant information from previous frames. This reduces the amount of new processing required and leverages temporal redundancy to simplify the filtering process.
3Loss of information
If motion compensation is applied during filtering, then moving objects are preserved, but processing time increases
Solution Approach 1:
The patent applies motion compensation selectively to blocks where motion is detected, rather than processing every block with full motion estimation. This partial action approach preserves moving objects while reducing overall processing time by skipping unnecessary computations in stationary regions.
Data Source
AI summary
Several systems and methods for filtering noise from a picture in a picture sequence associated with video data are disclosed. In an embodiment, the method includes accessing a plurality of pixel blocks associated with the picture and filtering noise from at least one pixel block from among the plurality of pixel blocks. The filtering of noise from a pixel block from among the at least one pixel block includes identifying pixel blocks corresponding to the pixel block in one or more reference pictures associated with the picture sequence. Each identified pixel block is associated with a cost value. One or more pixel blocks are selected from among the identified pixel blocks based on associated cost values. Weights are assigned to the selected one or more pixel blocks and set of filtered pixels for the pixel block is generated based on the weights.