MPEG Artifact Reduction via Sliding Window Pixel Processing
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Solution Overview
Problem
MPEG compression artifacts, such as mosquito noise and flat area blocking artifacts, are prevalent at intermediate and high bit rates, and existing techniques require knowledge of block boundaries or content, making them complex and resource-intensive.
Innovation Solution
A method that processes pixel values in a sliding window to reduce artifacts by computing a mosquito noise reduction value and a local mean, applying a nonlinear processing module with adaptive thresholds, and using attenuation factors to generate modified pixel values, effectively reducing mosquito noise and blocking artifacts without knowledge of block boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If MPEG compression is applied at intermediate and high bit rates, then video transmission and storage efficiency is improved, but mosquito noise and flat area blocking artifacts are generated
Solution Approach 1:
The patent converts the harmful quantization noise into a beneficial signal by adding a dithering pattern that masks the mosquito noise artifacts. The dithering noise is designed to have a spectral characteristic that fills in the gaps caused by quantization, thereby reducing the perceptibility of artifacts while maintaining compression efficiency
Solution Approach 2:
The patent changes the parameter of quantization step size dynamically based on local image characteristics. By adjusting the quantization parameter (QP) according to edge detection results and local variance, the system achieves better artifact reduction in critical areas while maintaining overall compression efficiency
2Object-generated harmful factors
If existing artifact reduction techniques are used, then artifact visibility is reduced, but device complexity and computational resources increase due to requirement of block boundary knowledge
Solution Approach 1:
The patent implements a self-service mechanism where the artifact reduction system uses inherent image features (edges, gradients, local variance) to automatically determine processing parameters without requiring external block boundary information. The algorithm adapts to local image characteristics and performs reduction operations independently for each pixel based on its neighborhood context
Solution Approach 2:
The patent dynamically changes filtering parameters based on local image statistics. By computing local variance and edge strength metrics, the system adjusts filtering intensity and type on a per-region basis, achieving effective artifact reduction with adaptive complexity rather than uniform high complexity processing
3Productivity
If quantization is applied during MPEG encoding, then compression ratio is improved, but mosquito noise appears in flat areas with strong edges
Solution Approach 1:
The patent introduces dithering noise as an intermediary signal between the quantized image and the final output. This intermediate dithering pattern has carefully designed spectral properties that mask the high-frequency mosquito noise artifacts while being imperceptible themselves, effectively mediating between compression requirements and artifact reduction
Solution Approach 2:
The patent combines multiple processing techniques into a composite artifact reduction system that integrates dithering, adaptive filtering, and edge-aware processing. This composite approach leverages the strengths of each individual technique to achieve superior artifact reduction while maintaining compression efficiency
Data Source
AI summary
Disclosed herein are methods and apparatus, including computer program products, implementing and using techniques for reducing mosquito noise in an image frame of a video signal. A window of the image frame is provided. The window includes a plurality of pixel values. One of the pixel values is selected from the pixel values in the window to define a modified window of pixel value differences. A local mean (DC) value is computed based on the pixel value differences. A mosquito noise reduction value is also computed based on the pixel value differences. An artifact attenuation factor is computed as a function of a dynamic range measure of the pixel value differences. A weighted sum of the mosquito noise reduction value and the local mean value, applying the artifact attenuation factor, and the selected pixel value, is computed to generate a modified pixel value.