Image Sensor Matrix Using Segmented Blocks for Parallel Readout
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Solution Overview
Problem
Large-sized image sensors and matrix displays face challenges in organizing pixels and row decoders as the number of rows increases, and photolithography techniques limit exposure, requiring complex and inefficient production methods.
Innovation Solution
The matrix is organized into identical blocks, each containing rows of pixels and row decoders, with column conductors linking to specific read circuits, allowing for simultaneous reading of multiple rows and reducing production complexity by using a single mask for identical blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of moving object
If the number of rows in the image sensor increases, then the sensor size and resolution improve, but the reading speed decreases and organization becomes more complex
Solution Approach 1:
The matrix is divided into multiple identical blocks, each block containing a subset of rows and its own row decoder. This segmentation allows parallel reading operations across multiple blocks simultaneously, maintaining high reading speed while enabling large sensor size through modular organization.
Solution Approach 2:
The patent introduces a block dimension in addition to rows and columns. By organizing pixels into P blocks where each block contains M rows, the system adds a spatial dimension for parallel processing, enabling simultaneous reading from multiple blocks to achieve high speed despite large total row count.
2Quantity of substance
If the number of rows increases, then the sensor capacity improves, but the organization complexity increases
Solution Approach 1:
The sensor is segmented into P identical blocks, each with M rows and N columns. This segmentation reduces organization complexity by creating repeating modular units that can be independently addressed, allowing large sensor capacity through simple repetition of standardized blocks rather than complex unique addressing for each row.
Solution Approach 2:
Each block is designed to be universal and identical to others, with the same structure and functionality. This universality simplifies organization by allowing the same control logic and decoder design to be applied repeatedly across all blocks, reducing overall system complexity while achieving high sensor capacity.
3Area of stationary object
If photolithography uses stitching technique for large surfaces, then large sensor production becomes possible, but production complexity and steps increase
Solution Approach 1:
The sensor design segments the matrix into P identical blocks that can be independently exposed during photolithography. This allows the use of a single reusable mask for each block type, simplifying manufacturing by enabling sequential exposure of identical blocks without requiring complex custom masks for each region, thus reducing production complexity while achieving large surface area.
Solution Approach 2:
The identical block structure enables copying the same photolithography mask pattern across multiple blocks. Instead of creating unique masks for each region (which would increase production complexity), the same mask design is copied and applied to all P blocks, significantly simplifying the manufacturing process for large surface area sensors.
Data Source
AI summary
The invention relates notably to large-sized image sensors or image sensors with a large number of rows. Each column of pixels is organized in P superposed blocks. A row decoder organized as P identical decoders selects one row out of M in each of the P blocks. Each block is linked to one respective column conductor out of P column conductors. P read circuits CL1 to CL4 are placed at the foot of each column of pixels and each is connected to a respective column conductor. The signals from the P rows selected by the decoder can be extracted simultaneously or else they can be selected by a specific decoder which selects one read circuit out of the P read circuits of each column. The matrix can be produced by photolithography, by abutting identical matrix portions, for example P different portions corresponding to P identical regions ZB1 to ZB4.