Image Sensor Noise Removal Circuit Using Pixel Segmentation
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Solution Overview
Problem
Image sensors face challenges in accurately sensing images due to noise components generated by photocharge elements, which degrade image quality and require efficient noise removal methods.
Innovation Solution
An image sensor with a noise removing circuit that includes a storage unit and a noise removing unit, utilizing transistors and capacitors to sample and adjust photocharge corresponding to noise components, allowing for effective noise removal during image sensing operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If photo sensitive elements are used to detect optical signals, then image sensing capability is achieved, but noise components are generated that degrade image quality
Solution Approach 1:
The pixel is divided into two distinct regions: a photo sensitive device (PSD) region for generating photocharges from optical signals, and a storage unit region for holding noise component photocharges. This spatial segmentation allows the sensing function and noise storage function to operate independently, enabling noise removal without compromising image sensing accuracy.
Solution Approach 2:
The noise component is extracted from the total photocharge signal by sampling it separately in the storage unit during a predetermined period when no optical signal is present. This extracted noise component is then subtracted from the signal-containing photocharges, effectively removing the harmful noise while preserving the useful image information.
2Reliability
If noise removing circuit is added to each pixel, then noise removal capability is improved, but device complexity increases
Solution Approach 1:
The noise removing circuit is merged with the existing pixel structure, sharing common elements such as the photo sensitive device and electrical connections. The storage unit is integrated into the pixel array, with its capacitance formed using the same semiconductor substrate and doping techniques, thereby reducing overall device complexity while maintaining effective noise removal capability.
Solution Approach 2:
The storage unit serves multiple functions: it stores noise component photocharges during the sampling period, maintains this stored charge during the signal acquisition period, and enables noise subtraction. This multi-functionality reduces the need for separate dedicated noise removal components, simplifying the overall device structure.
3Measurement precision
If storage unit is used to sample and store noise photocharge, then noise component can be removed, but manufacturing precision requirements increase
Solution Approach 1:
The storage unit capacitance is formed by controlling the doping concentration and depth of a specific region in the semiconductor substrate, rather than requiring precise fabrication of discrete capacitor components. By adjusting doping parameters (concentration, depth, area), the capacitance value can be tuned to achieve accurate noise sampling without imposing stringent manufacturing precision requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables more accurate image sensing by effectively removing noise components, improving image quality without the need for additional post-processing steps, thereby enhancing the efficiency of image sensing.
Implementation Method 1
a photo sensitive device (PSD) for generating photocharges
Data Source
AI summary
An image sensor including a noise removing unit may sense images accurately by measuring the amount of noise generated when the image sensor does not perform a sensing operation, storing information about the measured noise amount in each pixel, and removing photocharge corresponding to the information about the measured noise amount during image sensing.