Bayer Pattern Video Signal Bad Pixel Interpolation
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Solution Overview
Problem
Conventional digital video signal processing systems using Bayer-pattern solid-state image sensing devices suffer from distortion issues such as aliasing, color moiré, loss of detail, and false colors due to inadequate interpolation of high-frequency areas, particularly at edges, leading to poor visual quality in images displayed on devices like cellular telephones and digital still cameras.
Innovation Solution
A video signal processing method and apparatus that detects bad pixels by generating a pixel information signal based on differences with neighbor pixels, using threshold comparisons and average variance calculations to determine whether a pixel is good or bad, and interpolates these bad pixels using neighbor data to improve image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional interpolation schemes are used to process Bayer-pattern digital video signals, then the processing complexity is low, but the image quality deteriorates with distortion, aliasing, color moiré, and loss of detail
Solution Approach 1:
The patent segments the interpolation process into two distinct stages: first identifying bad pixels through statistical analysis of neighbor pixel differences, then interpolating only the identified bad pixels rather than processing all pixels uniformly. This segmentation allows complex processing to be focused only where needed, improving image quality without proportionally increasing overall processing complexity
Solution Approach 2:
The patent performs preliminary detection and identification of bad pixels before performing interpolation. By using statistical methods to pre-identify which pixels require correction based on differences from neighbor pixels, the system prepares the data in advance, allowing subsequent interpolation to be more targeted and effective, thereby improving image quality while managing processing complexity
2Manufacturing precision
If high-frequency areas such as edges are not appropriately interpolated, then the processing speed is high, but the image quality deteriorates with aliasing, color moiré, and loss of detail
Solution Approach 1:
The patent applies different processing approaches to different regions of the image based on local characteristics. By analyzing differences between neighbor pixels and identifying areas with high variance or abnormal values, the system applies interpolation only where needed (at edges and high-frequency areas), rather than uniformly processing the entire image. This local quality approach maintains processing speed while improving image quality in critical regions
Solution Approach 2:
The patent changes the processing parameters dynamically based on local image characteristics. By calculating statistical parameters such as mean and variance of pixel differences in different regions, the system adapts its interpolation approach to match local frequency content, applying more aggressive correction in high-frequency areas while maintaining speed in uniform regions
Data Source
AI summary
Provided are a method and apparatus for processing a Bayer pattern digital color video signal, where the video signal processing apparatus includes a BP detector that generates the pixel information signal PIS representing whether the current pixel is good or bad from the input video data based on the difference between the current pixel data and neighbor pixel data, and an interpolator that interpolates the bad pixel using neighbor pixel data in response to the pixel information signal.