CMOS Image Sensor Row Noise Reduction via Pixel-Level Offset Correction
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Solution Overview
Problem
Row noise reduction in CMOS image sensors using row-by-row based offset correction methods is sensitive to estimation errors and requires significant memory and processing time, making it inefficient and unsuitable for CMOS sensors with Color Filter Arrays (CFAs).
Innovation Solution
Determining row noise offset on a pixel-by-pixel basis using a two-dimensional region of pixels surrounding each central pixel, reducing memory requirements and sensitivity to offset estimation errors, and allowing effective noise reduction in sensors with and without CFAs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If row-by-row based offset correction is used to reduce row noise, then row noise can be corrected, but the method is very sensitive to errors in offset estimation and increases visible image defects
Solution Approach 1:
The patent divides the row noise correction process into pixel-level segments rather than processing entire rows uniformly. Each pixel's offset is estimated independently using local statistics from its neighborhood, breaking the global row-by-row correction into smaller, more manageable pixel-level units that are less sensitive to estimation errors
Solution Approach 2:
The patent applies local quality by using a two-dimensional region around each pixel to collect statistics for offset estimation, rather than using global row statistics. This local approach adapts to local variations in the image content and noise characteristics, making the correction more accurate and less sensitive to errors in any single pixel's offset estimation
2Object-affected harmful factors
If row-by-row correction method is used, then row noise can be reduced, but the entire row of pixels must be stored in memory during statistical analysis, increasing physical memory requirements and processing time
Solution Approach 1:
The patent segments the memory requirements by processing pixels independently rather than storing entire rows in memory. Each pixel's correction can be computed using only the local two-dimensional region around that pixel, eliminating the need to hold large portions of image data in memory simultaneously
Solution Approach 2:
The patent transitions from the traditional row-by-row (one-dimensional) processing approach to a two-dimensional local region approach. By collecting statistics from a 2D neighborhood around each pixel rather than from an entire row, the method reduces the memory footprint required for statistical analysis while maintaining noise correction effectiveness
3Object-affected harmful factors
If row-by-row noise correction is applied, then row noise can be reduced, but it requires passing all lines and pixels as if they have uniform color response, making it inappropriate for CMOS sensors with Color Filter Arrays
Solution Approach 1:
The patent applies local quality by estimating offsets separately for different color channels at each pixel location rather than applying a uniform row-wide offset. This allows the method to accommodate the non-uniform color response characteristics of CFA sensors, where different pixels have different color filtering properties
Solution Approach 2:
The patent segments the correction approach by color channel and pixel location, rather than applying a single uniform correction to an entire row. This segmentation allows the method to handle the heterogeneous color responses of CFA sensors effectively
Data Source
AI summary
A method for reducing the row noise from complementary metal oxide semiconductor (CMOS) image sensor by using a local offset correction is disclosed. The method operates on sensor with and without a Color Filter Array (CFA) before any interpolation is applied and estimates the local offset by comparing the rows in a local window. The method also reduces the pixel-to-pixel noise while reducing the row noise.