Bad Pixel Correction in Image Sensors via Patch Normalization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Digital cameras with CCD or CMOS image sensors face reduced image quality due to malfunctioning pixel sensors, known as bad pixels, which existing methods fail to effectively correct.
Innovation Solution
A method and apparatus that utilize a digital signal processor to detect bad pixels by determining the color of a center pixel in a Bayer patch, extracting main and auxiliary patches, generating a normalized patch to match the level of the main patch, and identifying corrupted pixels using energy minimization techniques to determine if the center pixel is bad.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing bad pixel correction methods are used, then processing speed may be maintained, but detection accuracy and image quality deteriorate due to inability to effectively identify and correct malfunctioning pixels
Solution Approach 1:
The image is divided into multiple patches, each containing a center pixel and surrounding neighboring pixels. This segmentation allows for localized analysis of each patch to detect bad pixels individually, improving detection accuracy without requiring complex global processing of the entire image.
Solution Approach 2:
The patent introduces an intermediary calculation process that uses neighboring pixels as mediators to detect and correct bad pixels. By comparing the center pixel with its neighbors and using the neighbors to interpolate the correct value, the system achieves accurate bad pixel correction without directly complex analysis of the malfunctioning pixel itself.
2Manufacturing precision
If simple correction methods are used, then processing speed is maintained, but image quality deteriorates due to loss of detail and smoothness in corrected regions
Solution Approach 1:
The patent applies local quality by treating each patch independently with customized correction based on its specific neighboring pixels. The correction process considers the local characteristics of each region, maintaining smoothness and detail in the corrected areas while adapting to local variations in the image content.
Solution Approach 2:
The system performs preliminary identification of bad pixels by analyzing patches before final correction. By pre-identifying which pixels are malfunctioning and planning the correction approach for each patch, the system optimizes processing efficiency while ensuring high-quality correction results.
3Measurement precision
If advanced detection algorithms are implemented, then bad pixel detection accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent applies partial action by focusing computational resources only on patches containing potential bad pixels rather than processing the entire image uniformly. By identifying and correcting only the necessary portions, the system achieves high detection accuracy while minimizing overall computational energy consumption.
Data Source
AI summary
A method of detecting a bad pixel in an image sensor includes: determining, a first color of a center pixel of a Bayer patch output by the image sensor; extracting, a main patch, a first auxiliary patch, and a second auxiliary patch from the Bayer patch, having the first color, a second other color, and a third other color, respectively; generating a normalized patch of the first color from the main patch and the auxiliary patches that brings a level of the auxiliary patches to a level of the main patch; and detecting whether the center pixel of the Bayer patch is a bad pixel using the normalized patch.