Gray Code Counter Shifting for Compact Low-Noise Image Sensors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing image sensors face challenges in minimizing the area occupied by counters while obtaining multiple samples, which increases the number of circuits and noise reduction is necessary for effective image processing.
Innovation Solution
The proposed solution involves a counter that generates binary codes by comparing pixel signals with a ramp signal, performing shifting operations on reset binary codes to calculate digital signals, and using a reset memory circuit to store sum values, thereby minimizing the counter's area and reducing noise through a low-noise RSS readout operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a counter individually stores all the sampling results to obtain multiple samples, then the sampling capability is improved, but the area occupied by the counter increases due to increased number of circuits
Solution Approach 1:
The patent merges multiple sampling operations into a single counter by combining multiple samples through addition operations. The counter stores only the sum of multiple samples rather than each sample individually, reducing the number of circuits needed while maintaining the capability to obtain multiple samples through the summation result
Solution Approach 2:
The counter is designed to perform multiple functions: it can accumulate multiple samples through addition, store the summed result, and support shifting operations to extract individual sample values when needed. This multi-functional design allows a single counter to replace what would traditionally require multiple separate storage circuits
2Device complexity
If the counter area is minimized by reducing circuits, then the device complexity is reduced, but the noise reduction capability may be affected
Solution Approach 1:
The patent replaces complex physical storage structures with computational operations. Instead of using multiple separate counter circuits to store individual samples, the system uses addition operations to combine samples and stores only the sum, reducing physical circuit complexity while maintaining sampling capability through mathematical operations
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 allows for reduced noise in image data generation and faster auto focusing, increasing the frame rate by minimizing the counter's area and efficiently processing pixel signals.
Implementation Method 1
The CMOS image sensor may include pixels composed of CMOS transistors and may convert light energy into an electrical signal by using a photoelectric conversion element included in each pixel
Implementation Method 2
a counter generates a binary code corresponding to a result of comparing a pixel signal output from a plurality of pixel groups of a pixel array with a ramp signal
Implementation Method 3
a reset memory circuit configured to store a sum of N reset binary codes, each of the N reset binary codes corresponding to a result of comparing a reset signal of the pixel signal with the ramp signal, and to calculate one of the N reset binary codes by performing a shifting operation on the sum of the N reset binary codes
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Disclosed is a counter which generates a binary code and a digital signal. The counter includes: a reset memory circuit (270) configured to store a sum of N reset binary codes, each of the N reset binary codes corresponding to a result of comparing a reset signal of the pixel signal with the ramp signal, and to calculate one of the N reset binary codes by performing a shifting operation on the sum of the N reset binary codes; and an output memory circuit (280) configured to output the digital signal based on the N reset binary codes, a first image binary code indicating a result of comparing a first image signal of the pixel signal with the ramp signal once, and N sum binary codes, the N sum binary codes respectively indicating N results of comparing a sum signal of the pixel signal with the ramp signal.