Address Mapped Repartitioned Digital Pixel Sub-Frame Residual Accumulation
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Solution Overview
Problem
Conventional digital pixel architectures face challenges in maintaining image resolution and stability due to image motion, leading to smear and signal loss, as they often rely on in-pixel counters and orthogonal transfer methods that increase complexity and power consumption.
Innovation Solution
The address-mapped repartitioned digital pixel architecture introduces sub-frame residual accumulation and off-ROIC correction, using separate digital memory to stabilize the image and enhance resolution by mapping pixel data to multiple memory locations, allowing for more robust stabilization and increased effective resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If in-pixel counters and orthogonal transfer methods are used to accumulate charge, then the effective integration range is extended, but the device complexity and power consumption increase
Solution Approach 1:
The patent divides the pixel array into blocks and processes them sequentially through shared readout circuitry, rather than having full readout capability in each pixel. This segmentation allows charge accumulation without requiring complex in-pixel counters, reducing overall device complexity while maintaining integration range.
Solution Approach 2:
The patent merges the readout circuitry for multiple pixels into shared column and row wires, combining functions that would otherwise require separate circuitry in each pixel. This consolidation reduces device complexity and power consumption while preserving the ability to accumulate charge over extended integration ranges.
2Duration of action of moving object
If in-pixel counters and orthogonal transfer methods are used to accumulate charge, then the effective integration range is extended, but the power consumption increases
Solution Approach 1:
The patent merges the readout circuitry for multiple pixels into shared column and row wires, combining functions that would otherwise require separate circuitry in each pixel. This consolidation reduces device complexity and power consumption while preserving the ability to accumulate charge over extended integration ranges.
Solution Approach 2:
The shared readout circuitry serves multiple pixels simultaneously, making the circuitry universal rather than dedicated to individual pixels. This multi-functionality reduces the total power consumption compared to having separate counters and transfer mechanisms in each pixel.
3Measurement precision
If address mapping is used to map pixel data to multiple memory locations, then the spatial resolution is enhanced, but the device complexity increases
Solution Approach 1:
The patent uses address mapping to project pixel data onto a virtual grid with higher spatial resolution by utilizing multiple memory locations. This effectively adds a dimensional layer of resolution enhancement without requiring physical subdivision of pixels, achieving super-resolution through logical rather than physical means.
Solution Approach 2:
The patent creates multiple copies of pixel data in different memory locations through address mapping, where each location contributes to reconstructing the image at higher resolution. This copying approach enables resolution enhancement without requiring additional physical sensors.
4Measurement precision
If sub-frame residual accumulation is implemented, then the intensity resolution is matched to spatial resolution, but the device complexity increases
Solution Approach 1:
The patent divides the integration period into sub-frames and processes residuals from each sub-frame separately through shared circuitry. This segmentation allows intensity resolution matching to spatial resolution without requiring complex simultaneous processing in each pixel, reducing overall circuit complexity.
Solution Approach 2:
The patent performs preliminary accumulation of charge during sub-frame intervals, then processes the residuals in a second stage. This preliminary action separates the intensity measurement from the final readout, enabling matched resolution without requiring complex real-time processing circuitry in each pixel.
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 effectively matches intensity resolution to spatial resolution, reducing image smear and increasing the effective resolution of the detector array by allowing energy from the same scene point to be accumulated across multiple pixels, thereby improving modulation transfer function and dynamic range.
Implementation Method 1
a photo-diode that generates a pixel signal in response to incident photons
Implementation Method 2
the charge is accumulated on a capacitive element that effectively integrates charge, producing a voltage
Data Source
AI summary
The accumulation of registered sub-frame residuals in an address-mapped repartitioned digital pixel matches the intensity resolution (dynamic range) to the spatial resolution of the image. The digital accumulation of pixel quantization events (QEs) is extended to include sub-frame residuals. After all QEs are digitally accumulated, then removed from the analog accumulator, an analog residual value remains. Residual capture logic is configured to trigger residual digitization logic at least twice per frame interval for selected pixels to capture, digitize and then clear the residual value on the storage device. Memory update logic is configured to accumulate the quantization event digital values and residual digital values into existing digital values at the address-mapped memory locations in digital memory. Resolution enhancement is enabled by an address mapping that maps a one-pixel spacing on the detector to two or more pixel spacing in the digital memory.