Demosaicing Edge Directionality Detection in Image Sensors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image sensor demosaicing techniques, such as those using the Hamilton edge classifier and 9×9 kernel, struggle to accurately interpolate color information in high-frequency regions, particularly where successive 1-line narrow edges exist, leading to errors in edge directionality and image quality.
Innovation Solution
A color demosaicing apparatus and method that includes a missing green information extractor with a gradient calculating unit, line edge determining unit, directionality determining unit, edge classifying unit, and edge refining unit, which uses a kernel-based approach to differentiate between plain, successive 1-line, vertical, horizontal, and texture edge regions, and modifies edge directionality using thresholds to improve accuracy in edge sensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional edge sensing methods (Hamilton edge classifier) are used for demosaicing, then the process is simple and fast, but edge directionality detection is inaccurate in high-frequency regions with successive 1-line narrow edges
Solution Approach 1:
The patent segments the edge detection process into multiple stages: initial edge sensing using Hamilton classifier, followed by verification using 9×9 kernel variance calculation, and final classification into different edge types (successive 1-line narrow edges, vertical edges, horizontal edges, texture regions). This segmentation allows accurate detection in high-frequency regions while maintaining simplicity in low-frequency regions.
Solution Approach 2:
The patent performs preliminary edge sensing using the Hamilton classifier before applying the more complex 9×9 kernel variance method. This preliminary action identifies potential edge regions that require further verification, avoiding unnecessary complex processing in non-edge regions and improving overall efficiency.
2Measurement precision
If 9×9 kernel variance method is used for edge sensing, then edge detection accuracy improves, but processing time and computational complexity increase
Solution Approach 1:
The patent applies different processing strategies to different regions of the image based on local characteristics. The 9×9 kernel variance method is applied only to regions identified as potential edges by the Hamilton classifier, while non-edge regions use the simpler Hamilton method. This local quality approach maintains high accuracy where needed while reducing overall processing time.
3Manufacturing precision
If simple interpolation is used for demosaicing, then processing speed is fast, but color accuracy and image quality deteriorate in high-frequency regions
Solution Approach 1:
The patent implements a dynamic demosaicing process that adapts to local image characteristics. The edge classification unit dynamically determines the appropriate interpolation strategy for each region: using variance-based edge sensing and directionality-aware interpolation in high-frequency edge regions, and simple interpolation in low-frequency regions. This dynamic approach maintains color accuracy in challenging regions while preserving overall processing speed.
Data Source
AI summary
An apparatus and method for demosaicing colors in an image sensor can accurately locate edge directionality by detecting a successive 1-line edge precisely. The embodiments may include an image sensor containing information on a color signal detected from each pixel, a first line memory receiving and storing output data from the image sensor, a missing green information extractor extracting missing green pixel information from the data of the first line memory, a delayer receiving the data of the first line memory, the delayer delaying the received data for a prescribed duration, the delayer outputting the delayed data, a second line memory temporarily storing the data outputted from the missing green information extractor and the data provided via the delayer, and a missing red/blue information outputter extracting missing red/blue information from the data of the second line memory.