Edge-Aware Remosaic Interpolation for N-Cell Image Sensors
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Solution Overview
Problem
Image sensors with n-cell patterns face challenges in remosaic processing due to increased pixel distances between color filters, making simple linear interpolation insufficient.
Innovation Solution
An image processing device and method that utilize different interpolation schemes based on edge detection to determine interpolation reference data, improving accuracy and quality of remosaic images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simple linear interpolation is used for remosaic processing, then the processing is simple and fast, but the interpolation accuracy is insufficient due to the long distance between pixels of the same color in n-cell pattern sensors
Solution Approach 1:
The patent applies local quality by detecting edge types (horizontal, vertical, diagonal, or none) in different regions of the image and selecting different interpolation schemes accordingly. For example, horizontal edge detection triggers horizontal interpolation using specific pixel combinations, while vertical edges use vertical interpolation. This localized adaptation ensures high interpolation accuracy in each region without uniformly applying complex processing to the entire image.
Solution Approach 2:
The patent changes interpolation parameters based on detected edge characteristics. When horizontal edges are detected, the interpolation uses pixel data from horizontally adjacent pixel groups with specific weighting coefficients. When vertical edges are detected, it switches to vertical interpolation with different coefficients. This dynamic parameter adjustment optimizes interpolation accuracy for each local region's structural characteristics.
2Manufacturing precision
If different interpolation schemes are used based on edge types, then the interpolation accuracy at edges is improved, but the processing complexity and computational load increase
Solution Approach 1:
The patent segments the image processing into distinct edge detection stages and interpolation stages. It first detects horizontal edges using pixel data from specific positions, then separately detects vertical edges, and finally applies corresponding interpolation schemes for each detected edge type. This segmentation allows the system to handle different edge characteristics with dedicated processing routines, improving edge accuracy while maintaining organized complexity.
Solution Approach 2:
The patent performs preliminary edge detection and classification before executing the interpolation process. By identifying horizontal, vertical, or diagonal edges in advance and determining the appropriate interpolation scheme beforehand, the system avoids complex real-time decision-making during interpolation. This preliminary action simplifies the overall processing flow while ensuring accurate edge handling.
3Reliability
If advanced interpolation methods are used to handle the long pixel distance, then the remosaic quality improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by selectively using advanced interpolation schemes only in regions where edges are detected, while using simpler interpolation methods in flat regions. For example, when no edge is detected in a region, the system can use basic interpolation, reserving computationally intensive edge-aware interpolation only for regions requiring it. This partial application reduces overall processing time while maintaining high quality where necessary.
Data Source
AI summary
An image processor, and an image processing method, includes an acquirer configured to acquire first pixel data from a first pixel group corresponding to a first color, and acquire second pixel data and third pixel data from a second pixel group and a third pixel group, respectively, which are arranged on both sides of the first pixel group and correspond to a second color. The image processor also includes a determiner configured to determine one of second pixel data and third pixel data as interpolation reference data using different schemes depending on a type of edge detected based on a difference in the first color and the second color in an image region corresponding to the first pixel data. The image processor further includes an interpolator configured to interpolate a part of the first pixel data to correspond to the second color based on interpolation reference data.