Digital Imager Noise Filtering and White Balancing
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Solution Overview
Problem
Conventional image processing pipelines fail to effectively remove noise and artifacts introduced by digital imagers, and do not adequately compensate for lighting conditions or sensor color responsivity, leading to suboptimal image quality.
Innovation Solution
A method that involves noise filtering to remove column noise and single pixel defects, white balancing to adjust for lighting conditions, and dynamic remapping to optimize image data for display, using techniques such as column fixed pattern noise correction, directional filtering, and scalar color adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image processing pipelines are used, then basic image data processing is achieved, but noise and artifacts introduced by digital imagers are not effectively removed
Solution Approach 1:
The patent performs preliminary actions by measuring and characterizing noise and artifacts during factory calibration before the imager is delivered to the customer. Offset values and gain values are pre-determined through controlled measurements during manufacturing, allowing these correction parameters to be stored and applied automatically during normal operation without requiring additional measurement time or complex real-time analysis.
Solution Approach 2:
The patent implements feedback mechanisms where the imager continuously monitors its own performance characteristics and automatically applies corrections using stored calibration data. The system uses feedback from initial characterization measurements to generate correction values that are then applied to subsequent image data, creating a closed-loop system that compensates for noise and artifacts without requiring manual intervention.
2Measurement precision
If conventional image processing is used, then basic processing functions are provided, but adequate compensation for lighting conditions and sensor color responsivity is not achieved
Solution Approach 1:
The patent performs preliminary characterization of the imager's response to lighting conditions and color filters during factory calibration. Spectral sensitivity data and color filter transmission characteristics are measured in advance, creating lookup tables and correction parameters that simplify real-time processing. This preliminary action allows complex compensation calculations to be pre-computed and stored, reducing the computational burden during actual image capture.
Solution Approach 2:
The patent introduces intermediary correction parameters and lookup tables that mediate between the raw imager data and the final corrected image. These intermediaries include offset values, gain values, and color correction matrices that translate complex physical measurements into practical correction operations, simplifying the overall processing architecture while maintaining high measurement precision.
3Reliability
If noise filtering and correction processes are added, then image quality is improved, but processing time and computational requirements increase
Solution Approach 1:
The patent performs all complex noise characterization and correction calculations during factory calibration before the imager is deployed. By pre-measuring noise patterns, fixed pattern noise, and other artifacts under controlled conditions, the system creates stored correction data that can be applied quickly during normal operation without requiring time-consuming real-time analysis, thus improving image quality without significantly increasing processing time.
Data Source
AI summary
A system and method process non-linear image data, still or video, from a digital imager. Noise generated by analog-to-digital converters is filtered from a pixel of digital image data. Moreover, the effects of single pixel defects in the imager are eliminated by clamping a predetermined pixel of image data within the window when the value of the predetermined pixel is greater than a maximum value of the image data of neighboring pixels or less than a minimum value of the image data of neighboring pixels. Ripples in image data are reduced by eliminating the effects of single pixel defects before filtering for crosstalk caused by electrical crosstalk between sensor elements in an imager. Dark current is removed from image data generated by an imager by subtracting a fraction of a determined dark current value from all image data generated by the imager to compensate for nonlinearities in dark current across the imager. The image data is white balanced by creating a set of scalar color adjustments from determined average color values and constraining the set of scalar adjustments to plausible lighting conditions to prevent overcompensation on images having large regions of similar hue. Lastly, utilization of a fixed set of intensity levels is optimized by remapping and restreching the image data to create new luma values for each pixel.