UV Sensor Pixel Compensation via Kernel Centroid Analysis
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Solution Overview
Problem
Ultraviolet (UV) sensor arrays face significant performance reduction due to dead or stuck pixels, for which existing solutions are inadequate in providing accurate replacement values, particularly since current methods are designed for visible sensor arrays and do not effectively address the unique challenges of UV sensor arrays.
Innovation Solution
A method and system that estimate values for inoperable pixels in UV sensor arrays by applying a kernel, calculating a centroid value, and using a compensation algorithm that employs filters such as Guard Peak, Median, Max Kernel Slope, and Max Corner, based on specific centroid value ranges to minimize noise and accurately replace pixel values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing solutions for visible sensor arrays are applied to UV sensor arrays, then the method is simple to implement, but the accuracy of replacement values for inoperable pixels is insufficient
Solution Approach 1:
The patent applies parameter changes by adapting the compensation algorithm to UV-specific characteristics. It uses UV-appropriate kernel dimensions (3x3, 5x5, 7x7) and adjusts centroid value thresholds specifically for UV sensor properties rather than using generic visible sensor parameters. The algorithm modifies replacement values based on UV radiation characteristics and sensor-specific noise patterns.
Solution Approach 2:
The patent implements local quality by applying different compensation strategies to different regions of the sensor array based on their spatial relationship to inoperable pixels. It uses multiple kernel sizes (3x3, 5x5, 7x7) centered on inoperable pixels and applies weighted averages with position-dependent coefficients. The algorithm also applies different processing to edge regions versus center regions of the array, optimizing replacement values for each local area.
2Reliability
If simple replacement methods (zero or average of neighbors) are used, then the processing is fast and simple, but the noise reduction capability is insufficient and random sources appear in output
Solution Approach 1:
The patent implements feedback by using the centroid value (calculated from surrounding pixel values) to dynamically select and adjust the compensation strategy. The centroid value feeds back into the algorithm to determine which kernel size to use, which weighting scheme to apply, and whether to apply additional smoothing. This feedback loop continuously optimizes the replacement value based on the local signal characteristics.
Solution Approach 2:
The patent applies preliminary action by pre-calculating and storing multiple kernel configurations (3x3, 5x5, 7x7 matrices with different weighting patterns) before processing the sensor array. It also pre-establishes centroid value thresholds that trigger different compensation strategies. This preparation allows the system to quickly select appropriate processing parameters during actual operation without complex real-time calculations.
Data Source
AI summary
A method for estimating values lost to inoperable pixels on ultraviolet (UV) sensor arrays comprising identifying an inoperable pixel on a UV sensor array, applying a three by three kernel to the inoperable pixel, the three by three kernel being centered on the inoperable pixel, acquiring a centroid value for the inoperable pixel, applying a compensation algorithm based on the three by three kernel radial centroid value, and calculating estimated values for the inoperable pixel.