Digital Image Sensor Noise Calibration via Dark Frame Averaging
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Solution Overview
Problem
Traditional image sensors suffer from fixed pattern noise due to non-ideal effects of analog circuits, leading to vertical stripe phenomena and inconsistent signal characteristics, which existing noise cancellation circuits in the analog domain are over-complicated and costly to address.
Innovation Solution
A method and apparatus that calculate and store average pixel values in a test environment to create calibration values, which are then used in the digital domain to adjust pixel values and reduce fixed pattern noise in a normal light source environment, utilizing a storage circuit and control circuit with a lookup table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise cancellation circuits are implemented in the analog domain, then fixed pattern noise can be reduced, but the device complexity and manufacturing cost increase significantly
Solution Approach 1:
The patent replaces the mechanical/analog noise cancellation circuit with a digital signal processing approach. Specifically, it uses a digital-to-analog converter (DAC) to generate calibration signals and performs noise cancellation through digital computation of calibration values and pixel value adjustments, thereby eliminating the need for complex analog noise cancellation circuits and reducing device complexity while maintaining noise reduction effectiveness
Solution Approach 2:
The patent changes the operating parameters by moving the noise cancellation process from the analog domain to the digital domain. It generates calibration values through digital computation based on dark frame data, then applies these calibration values to correct pixel values in normal images through digital subtraction, thereby achieving noise reduction without requiring complex analog circuitry
2Object-affected harmful factors
If analog noise cancellation circuits are used, then fixed pattern noise is reduced, but production costs increase
Solution Approach 1:
The patent replaces expensive analog noise cancellation circuits with a digital implementation using a DAC and digital signal processing. The system generates calibration signals digitally, converts them to analog for sensor exposure, then performs digital computation to generate calibration values and apply corrections to normal images, thereby achieving noise reduction at lower production cost
Solution Approach 2:
The patent uses a DAC (digital-to-analog converter) as a temporary, programmable signal generation tool during the calibration process. The DAC generates the necessary analog signals for dark frame capture, but the actual noise cancellation is performed through disposable digital computation and storage of calibration values, eliminating the need for permanent, expensive analog noise cancellation circuitry
3Object-affected harmful factors
If analog domain signal processing is performed for noise cancellation, then noise reduction is achieved, but signal processing time is excessive
Solution Approach 1:
The patent performs preliminary calibration by capturing dark frames and computing calibration values in advance. The calibration values are stored and then directly applied to normal images through simple digital subtraction, eliminating the need for time-consuming real-time analog signal processing during normal image capture and reducing overall signal processing time
Data Source
AI summary
A method for reducing fixed pattern noise of an image sensor is provided. The method includes: accessing pixel data of at least one test frame in a test environment; and calculating/deriving average values of each column based on at least one portion of pixel data of the column in the at least one test frame, wherein the average values of columns are used as calibration values for calibrating image pixel data of columns when the image sensor operates in a normal light source environment.