Pseudo-Luminance Edge Detection for Bayer Pattern Pseudo-Color Suppression
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Solution Overview
Problem
Conventional digital image signal processing methods fail to accurately suppress pseudo-color components, leading to reduced image quality due to inaccurate edge detection and loss of high-frequency components, especially in high-frequency regions where aliasing occurs.
Innovation Solution
A digital image signal processing apparatus that interpolates Bayer pattern signals, generates pseudo-luminance values for edge detection, and uses a color suppression coefficient to suppress pseudo-color components in the chrominance signals, while compensating for edge detection errors using a compensator to enhance edge information and reduce pseudo-color occurrence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a low pass filter is used to attenuate high-frequency components to prevent aliasing, then aliasing is suppressed, but the cut-off frequency may be higher than the sampling frequency causing residual aliasing and pseudo-color artifacts
Solution Approach 1:
The patent introduces a pseudo-luminance generator as an intermediary component that creates a luminance signal from Bayer pattern data before edge detection. This intermediary signal serves as a bridge between the raw Bayer data and the final edge detection process, enabling more accurate edge detection without requiring aggressive low-pass filtering that would cause aliasing. The pseudo-luminance signal allows the system to detect edges in the original high-frequency Bayer data while avoiding the need for problematic filtering operations.
Solution Approach 2:
The patent replaces the conventional mechanical approach of using low-pass filters to prevent aliasing with a signal processing approach using pseudo-luminance generation. Instead of mechanically filtering out high-frequency components (which causes loss of detail and residual aliasing), the system substitutes this with generating a derived luminance signal that preserves edge information while eliminating the need for aggressive filtering. This substitution allows edge detection to proceed directly on Bayer pattern data without the trade-offs of traditional filtering.
2Ease of operation
If edge detection is performed using conventional methods without accurate luminance signals, then processing is simplified, but edge detection accuracy deteriorates leading to jagged outlines and stair-stepping artifacts
Solution Approach 1:
The patent changes the parameter used for edge detection from conventional approaches to a pseudo-luminance signal derived from Bayer pattern data. By transforming the detection parameter to use luminance information extracted from the Bayer pattern (rather than relying on interpolated RGB data or complex processing), the system achieves more accurate edge detection while maintaining processing efficiency. This parameter change enables accurate detection of high-frequency edges without the need for complex multi-step processing.
3Loss of information
If high-frequency components are retained in the digitized image, then image detail is improved, but pseudo-color artifacts increase due to aliasing in high-frequency regions
Solution Approach 1:
The patent extracts the harmful pseudo-color artifacts by detecting edges in the pseudo-luminance signal and using this edge information to identify regions where aliasing occurs. By separating the edge detection function from the color information processing, the system can identify and remove pseudo-color artifacts while preserving the high-frequency luminance details. The extraction of edge information allows the system to distinguish between genuine high-frequency content and aliasing-induced artifacts.
Solution Approach 2:
The patent converts the harmful aliasing effect into a beneficial edge detection opportunity. By using the pseudo-luminance signal to detect edges in the Bayer pattern data, the system can identify the locations of high-frequency edges and use this information to guide color suppression. The aliasing that would normally create harmful pseudo-color artifacts is instead utilized to identify where edge enhancement and color suppression are most needed, transforming the harmful high-frequency aliasing into a useful detection mechanism.
Data Source
AI summary
An apparatus for processing a digital image signal includes a pseudo-luminance generator configured to generate pseudo-luminance signals from the image signal. An edge detector detects an edge in the image signal using a part of an interpolated image signal as a luminance signal for a line of the image signal including a pixel subjected to edge detection and using the pseudo-luminance signals for adjacent lines. A color suppressor suppresses pseudo-color present in the chrominance component of the image signal in response to a detected edge. A compensator may be provided to generate a second edge metric relative to the image signal to compensate for an edge detection error occurring in the edge detector. A color suppression coefficient calculator to generate a color suppression coefficient using a first edge metric generated by the edge detector and the second edge metric. Corresponding systems and methods are disclosed.