Adaptive Demosaicing for Bayer Pattern Isolated Points
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Solution Overview
Problem
Existing demosaicing methods using Bayer patterns often introduce spurious resolution and false colors, especially near the resolution limit where pixel pitch matches the subject's fine details, due to inadequate evaluation of interpolation direction homogeneity.
Innovation Solution
An image processing apparatus performs interpolation in multiple directions, calculates evaluation values based on correlation between pixels, corrects evaluation values for isolated points, and selects the appropriate interpolation direction to generate accurate color signals, thereby reducing spurious resolution and false colors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If demosaicing is performed using basic interpolation methods (bilinear or bicubic), then the processing is simple and fast, but spurious resolution and false colors occur in images containing high frequency components
Solution Approach 1:
The patent applies dynamics by making the interpolation method adaptive rather than static. The system dynamically selects between different interpolation approaches based on local image characteristics (edge detection results), allowing the processing to adjust to varying frequency content and structural features across different regions of the image, thereby resolving the contradiction between speed and accuracy.
Solution Approach 2:
The patent changes the parameter of interpolation method selection based on local image properties. By detecting edges and determining their directions, the system modifies which interpolation algorithm is applied in different regions, using simple interpolation in non-edge areas for speed and direction-aware interpolation near edges for accuracy, thus resolving the speed-accuracy tradeoff.
2Manufacturing precision
If demosaicing is performed by using pixels along an edge direction, then spurious resolution and false colors are inhibited, but the determination of appropriate interpolation direction becomes complex near the resolution limit
Solution Approach 1:
The patent applies partial action by performing comprehensive edge detection and direction evaluation only where necessary (in regions with high frequency components or potential edge structures), rather than uniformly across the entire image. This reduces the overall computational complexity while maintaining accuracy where it matters most, resolving the contradiction between precision and complexity.
Solution Approach 2:
The patent segments the image processing into distinct stages: edge detection, direction determination, and conditional interpolation selection. By dividing the complex task into manageable segments and applying different processing strategies to different regions based on edge characteristics, the system reduces overall complexity while maintaining high interpolation accuracy.
3Measurement precision
If evaluation values are calculated for each pixel to determine interpolation direction, then appropriate interpolation can be selected, but isolated points with incorrect evaluation values cause inaccurate interpolation direction selection
Solution Approach 1:
The patent applies feedback by using the calculated evaluation values from peripheral pixels to correct and refine the evaluation value of the target pixel. This feedback mechanism allows the system to identify and correct isolated points with inaccurate evaluation values by comparing them against the consensus of surrounding pixels, thereby improving the reliability of interpolation direction selection.
Solution Approach 2:
The patent merges the evaluation information from multiple peripheral pixels to determine the correct interpolation direction for a target pixel. By combining the evaluation values from surrounding pixels and using them to correct isolated outliers, the system achieves more reliable direction selection that is robust against individual pixel anomalies.
Data Source
AI summary
At least one image processing apparatus is provided which allows performing a demosaicing process on a polychrome image signal with high accuracy. The at least one image processing apparatus performs an interpolation process in each of a plurality of defined directions on a mosaic image signal and acquires an evaluation value representing a correlation in each of a horizontal direction and a vertical direction for each of a plurality of pixels of the image signal having undergone the interpolation process. The evaluation values for at least one pixel of interest are corrected based on the evaluation values for peripheral pixels if a predetermined condition including a condition that it is determined that the at least one pixel of interest is an isolated point is satisfied. Then, the image signal after the at least one pixel of interest is interpolated based on the corrected evaluation values.