Compressed Per-Pixel Gain and Offset Noise Correction
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Solution Overview
Problem
Conventional black frame subtraction techniques for digital cameras are inefficient in reducing signal-dependent fixed pattern noise, require large memory storage, and cause camera startup delays due to the need for capturing and processing a large black frame, which is temperature-dependent and inaccurate at varying temperatures.
Innovation Solution
A method using per-pixel correction models calibrated at different illumination levels and temperatures, applying compressed gain and offset corrections to reduce noise, store smaller noise models, and calibrate during power down to avoid delays, incorporating signal-dependent and temperature-dependent correction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If black frame subtraction is used to correct fixed pattern noise, then signal-independent noise is reduced, but signal-dependent noise remains uncorrected and memory storage requirements increase
Solution Approach 1:
The fixed pattern noise correction is segmented into signal-independent component (corrected by black frame subtraction) and signal-dependent component (corrected by per-pixel gain/offset models). This segmentation allows each component to be handled by an appropriate correction method, reducing overall memory requirements while maintaining correction effectiveness.
Solution Approach 2:
The patent changes the correction parameters from storing complete black frame images to storing compressed per-pixel gain and offset values. This parameter transformation reduces memory storage requirements from megabytes per frame to kilobytes per pixel, while enabling correction of both signal-independent and signal-dependent noise components.
2Measurement precision
If a large black frame is captured and stored for noise correction, then fixed pattern noise can be reduced, but camera startup time increases
Solution Approach 1:
The per-pixel gain and offset correction parameters are pre-calibrated and stored in compact form, eliminating the need to capture and process large black frames at startup. This preliminary preparation of compressed correction data reduces startup time while maintaining noise correction capability.
Solution Approach 2:
Instead of capturing and storing complete black frame images, the patent uses compressed copies in the form of per-pixel gain and offset values. These compressed representations contain the essential correction information in a much smaller form, reducing both storage requirements and processing time.
3Measurement precision
If black frame subtraction is used for fixed pattern noise correction, then noise cancellation is achieved, but the correction is inaccurate at varying temperatures
Solution Approach 1:
The correction system is made dynamic by calibrating per-pixel gain and offset parameters at multiple temperature points and selecting or interpolating between them based on current sensor temperature. This dynamic adaptation maintains correction accuracy across varying temperatures, unlike static black frame subtraction.
Solution Approach 2:
The patent changes the correction approach by introducing temperature as a parameter that affects the correction values. By calibrating and storing temperature-dependent gain and offset parameters, the system adapts to temperature variations and maintains accurate noise correction across different operating conditions.
Data Source
AI summary
A method of pixel correction is disclosed. The method generally includes the steps of (A) calibrating a per-pixel correction model of a sensor at a plurality of different illumination levels, (B) generating a plurality of pixel values from the sensor in response to an optical signal and (C) generating a plurality of corrected values by applying the per-pixel correction model to the pixel values.