CFA Kernel Processing for Grid Pattern Noise Detection
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Solution Overview
Problem
Image sensors, particularly CMOS image sensors, suffer from grid pattern noise due to light scattering, which degrades image quality and can indicate sensor defects, and existing methods fail to effectively detect and remove this noise.
Innovation Solution
An image processing system and method that generates kernels corresponding to the N×N array pattern of a color filter array to detect and remove grid pattern noise by amplifying pattern pixel values and removing normal noise and textures irrelevant to the grid pattern, using a combination of kernels and image processing operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image processing methods are used, then general image processing is possible, but grid pattern noise cannot be effectively detected and removed
Solution Approach 1:
The patent segments the image processing task into distinct stages: generating detection kernels based on color filter array patterns, applying these kernels to extract grid pattern components, and separately processing normal image content. This segmentation allows targeted removal of grid pattern noise while preserving other image information, resolving the contradiction between noise detection accuracy and information loss.
Solution Approach 2:
The patent introduces detection kernels as an intermediary element that mediates between the raw image data and the final processed output. These kernels, generated based on the N×N array pattern of the color filter array, serve as a bridge to selectively identify and extract grid pattern noise without directly manipulating the original image pixels, thereby maintaining image quality while enabling accurate noise detection.
2Manufacturing precision
If grid pattern noise is removed, then image quality is improved, but additional processing time and complexity are required
Solution Approach 1:
The patent creates a universal processing framework where the same detection kernels and processing steps can handle various types of grid pattern noise regardless of the specific image content or lighting conditions. The kernel manager generates kernels based on the fundamental N×N array pattern, making the system multi-functional and adaptable to different scenarios without requiring separate processing pipelines, thus improving image quality without proportionally increasing system complexity.
Solution Approach 2:
The patent performs preliminary action by pre-generating detection kernels based on the known color filter array pattern before actual image processing. This preliminary preparation allows the main processing stage to simply apply these pre-computed kernels, significantly reducing the computational complexity during real-time operation while maintaining high image quality standards.
3Measurement precision
If detection kernels are generated based on N×N array pattern, then grid pattern detection accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-generating detection kernels based on the N×N array pattern of the color filter array before actual image processing occurs. This preprocessing step creates ready-to-use kernels that can be rapidly applied to images, improving detection precision while minimizing the time required during actual processing operations.
Solution Approach 2:
The patent uses copying by generating detection kernels that replicate the N×N array pattern structure of the color filter array. These kernel copies capture the essential grid pattern characteristics without requiring complex real-time analysis, enabling precise detection with reduced computational overhead and processing time.
Data Source
AI summary
An image processing device that reduces grid pattern noise in a captured image and which improves captured image quality may include an image input circuit configured to receive pixel values from an image sensor, a kernel manager configured to generate kernels corresponding to a grid pattern determined based on an N×N array pattern of a color filter array included in the image sensor, a preprocessor configured to perform a blur operation based on the pixel values and the kernels and to amplify pattern pixel values corresponding to the grid pattern, among the pixel values, and a grid pattern detector configured to change pixel values irrelevant to the grid pattern, among the pixel values, to a preset value based on the kernels and to generate a grid image including only the grid pattern.