Adaptive Quantization in Spatial Derivative Pixel Arrays
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Solution Overview
Problem
Conventional back-illuminated image sensors face issues with light leakage and low photodiode fill factor, leading to reduced signal-to-noise ratio and dynamic range, as well as limited power and bandwidth efficiency.
Innovation Solution
The image sensor is partitioned into blocks with anchor and non-anchor pixels, where anchor pixels are fully quantized and non-anchor pixels are quantized with a lower bit-depth, using anchor pixel statistics to adjust quantization parameters, thereby reducing bandwidth and power requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full quantization is performed on all pixels, then measurement precision is improved, but bandwidth and power consumption increase
Solution Approach 1:
The patent applies different quantization bit-depths to different regions of the image sensor. Specifically, anchor pixels (certain reference pixels) use higher bit-depth quantization to maintain precision, while non-anchor pixels use lower bit-depth quantization to reduce power consumption and bandwidth. This local differentiation resolves the contradiction by maintaining measurement precision where needed while reducing energy usage elsewhere.
Solution Approach 2:
The patent dynamically changes the quantization parameter (bit-depth) based on the pixel type and local image characteristics. By adjusting the quantization precision parameter according to the specific needs of different pixel regions, the system achieves optimal balance between measurement precision and power consumption without requiring full high-precision quantization across the entire sensor array.
2Measurement precision
If full quantization is performed on all pixels, then measurement precision is improved, but bandwidth consumption increases
Solution Approach 1:
The patent implements local quality by applying high bit-depth quantization only to anchor pixels and low bit-depth quantization to non-anchor pixels. This spatial differentiation of quantization precision reduces the total amount of data that needs to be transmitted, thereby reducing bandwidth consumption while maintaining adequate measurement precision in critical regions.
Solution Approach 2:
The patent extracts only the essential high-precision measurements from anchor pixels and uses them to represent or predict the values of surrounding non-anchor pixels. By separating the quantization process into different precision levels and using anchor pixel data to infer non-anchor pixel values, the system reduces overall bandwidth requirements while preserving critical measurement information.
3Measurement precision
If backside illumination is used to increase photodiode fill factor, then light capture is improved, but storage leakage increases
Solution Approach 1:
The patent segments the pixel array into distinct functional regions with different characteristics. By organizing pixels into blocks with designated anchor and non-anchor positions, the system can apply different processing and quantization strategies to different segments, thereby managing the trade-off between light capture efficiency and storage leakage effects in a controlled manner.
4Adaptability or versatility
If anchor pixel statistics are used to adjust quantization parameters, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements feedback by using anchor pixel statistics (such as mean, variance, or other statistical measures) to dynamically adjust the quantization parameters for non-anchor pixels. This feedback mechanism allows the system to adapt its quantization strategy based on actual image content and local characteristics, improving adaptability while keeping the complexity manageable through focused statistical analysis on a limited set of anchor pixels.
Solution Approach 2:
The patent performs preliminary action by pre-processing anchor pixel data to extract statistical information before using this information to guide the quantization of non-anchor pixels. This preliminary statistical analysis enables adaptive quantization parameters to be determined in advance for each region, improving versatility while organizing the complexity into a structured two-stage process.
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
This approach enhances the signal-to-noise ratio and dynamic range while reducing power and bandwidth consumption, making the image sensor more efficient in low-light conditions and versatile.
Implementation Method 1
Optical sensors are electronic detectors that convert light into an electronic signal
Data Source
AI summary
A photo sensor includes a plurality of pixel blocks, each including one or more anchor pixels and one or more non-anchor pixels. The anchor pixels produce first sensor signals and the non-anchor pixels produce second sensor signals. An amplifier circuit amplifies the first and second sensor signals. A variable bit-depth analog to digital converter (ADC) circuit quantizes amplified versions of the first sensor signals into first digitized sensor signals with a first bit-depth. The ADC circuit also quantizes amplified versions of the second sensor signals into second digitized sensor signals with a second bit-depth that is lower than the first bit depth. The second bit-depth may be selected based on anchor pixel statistics derived from the one or more first digitized sensor signals.