Dynamic Pixel Value Detection and Correction in Digital Cameras
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Solution Overview
Problem
Conventional digital color camera systems fail to correct defective pixel values generated during use or due to environmental factors like dust, leading to blurred and vague images, and require complex and costly circuitry for real-time correction.
Innovation Solution
A method and apparatus that dynamically detects and corrects pixel values in real time by subtracting examined pixel values from spatially adjacent reference values, using a comparator to determine errors and an adder/divider to replace incorrect values with an average, simplifying circuitry and integrating with existing color interpolation devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional correction methods are used (testing pixels before factory, recording defective positions), then manufacturing costs are reduced, but the system fails to correct defective pixels generated during use or due to environmental factors
Solution Approach 1:
The patent implements dynamic bad pixel detection by continuously comparing current pixel values with reference pixel values during operation, rather than using static pre-recorded defect positions. This allows the system to adapt to defects generated during use, such as dust-covered lenses or sensor degradation, making the correction system versatile for both manufacturing defects and runtime defects.
Solution Approach 2:
The patent pre-records reference pixel values from spatially adjacent pixels before correction is needed. These reference values are stored and used as benchmarks for detecting defective pixels during operation, enabling rapid correction without complex real-time computation.
2Reliability
If complex interpolation and correction operations are performed on all pixels, then defective pixel correction is achieved, but image quality deteriorates due to blurred and vague images
Solution Approach 1:
The patent applies correction operations selectively only to pixels identified as defective through comparison with reference values, rather than performing interpolation on all pixels. This localized approach preserves the quality of good pixels while correcting only the problematic ones, avoiding the blurred and vague images caused by universal interpolation.
Solution Approach 2:
The patent extracts and corrects only the defective pixel values from the image data stream, separating the correction process from the overall image processing pipeline. This allows the majority of pixels to remain untouched and preserve their original quality, while only the problematic pixels undergo correction.
3Productivity
If high-speed operating systems and complex circuitry are implemented for real-time correction, then dynamic pixel correction is achieved, but design and manufacturing costs increase
Solution Approach 1:
The patent uses simple subtraction and comparison operations that can be implemented with basic arithmetic logic units, replacing complex interpolation circuits. The method uses straightforward mathematical operations (subtraction, absolute value comparison) that require minimal computational resources, enabling real-time correction with simple and inexpensive circuitry.
Solution Approach 2:
The patent replaces complex mechanical/optical correction systems with electronic computational methods. By using digital subtraction and comparison of pixel values, the system achieves real-time correction through software-like logic implemented in hardware, eliminating the need for complex optical elements or mechanical adjustment mechanisms.
Data Source
AI summary
A pixel value array is provided, which includes an examined pixel value. Several reference pixel values are each subtracted from the examined pixel value to obtain several differences. The sampling pixels of these reference pixel values are spatially adjacent to the sampling pixel of the examined pixel value. The reference and examined pixel values represent the same color. The differences are compared with a reference value. When the absolute values of the differences are all greater than the reference value, the examined pixel value is determined as being wrong.