Motion Estimation Aided Noise Reduction in Video Encoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video encoding and decoding technologies face challenges in efficiently reducing noise in digital video streams while maintaining image quality, particularly in low-bandwidth communications, leading to potential blurring and artifacting.
Innovation Solution
The method employs motion estimation aided noise reduction encoding, which involves identifying a motion vector for a current block, using a noise reduction block to denoise the current block, generating a residual block, and encoding the denoised block, thereby minimizing noise while preventing blurring and artifacting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise reduction filtering is applied to video blocks, then noise is reduced, but image quality deteriorates due to blurring and artifacting
Solution Approach 1:
The patent applies noise reduction selectively based on motion characteristics. Blocks with low motion magnitude (below threshold) undergo noise reduction filtering, while blocks with high motion magnitude retain original pixels to avoid blurring. This local differentiation of processing quality resolves the contradiction by applying filtering only where it benefits image quality.
Solution Approach 2:
The patent dynamically adjusts noise reduction strength based on motion magnitude. The filtering operation is adapted to local motion characteristics - stronger filtering for static/low-motion areas, no filtering for high-motion areas. This dynamic adaptation prevents artifacting while maintaining noise reduction benefits.
2Measurement precision
If motion estimation is performed before noise reduction, then motion compensation accuracy improves, but processing complexity increases
Solution Approach 1:
The patent performs motion estimation before noise reduction to obtain accurate motion vectors. These motion vectors are used to identify corresponding pixels in reference frames for noise reduction filtering. This preliminary action ensures that noise reduction is applied to the correct spatial locations, maintaining motion compensation accuracy.
Solution Approach 2:
The patent extracts motion information (motion vectors) from the video sequence and uses it to guide the noise reduction process. By separating motion estimation as a preliminary step, the system can reuse this information without repeating full motion estimation during noise reduction, reducing overall complexity.
Data Source
AI summary
A method and apparatus for performing motion estimation aided noise reduction encoding and decoding are provided. Motion estimation aided noise reduction encoding can include identifying a motion vector for encoding a current block in a video frame based on a reference block in a reference frame, identifying a noise reduction block for denoising the current block, aligning the noise reduction block with the current block, denoising the current block, identifying a motion vector for encoding the denoised block, generating a residual block for encoding the denoised block, and encoding the denoised block. Denoising the current block can include identifying a filter coefficient for a pixel in the current block based on a corresponding pixel in the noise reduction block, producing a denoised pixel based on the coefficient and the corresponding pixel, and determining whether to use the denoised pixel or the current pixel for encoding the block.