RGBW Image Sensor Noise Reduction via Data Segmentation
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Solution Overview
Problem
Existing image pickup elements with RGBW pixels suffer from insufficient reduction of color noise in generated images, particularly when using signal outputs from these pixels.
Innovation Solution
The image pickup apparatus employs a signal processing unit that generates resolution data from one pixel group and color data from another, with up-conversion processing to enhance image resolution and reduce color noise by interpolating signals from surrounding pixels, particularly using a RGBW 12 array configuration where W pixels surround color pixels, thereby improving sensitivity and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RGBW pixels are used to increase sensitivity and obtain high S/N ratio images, then image sensitivity and signal-to-noise ratio are improved, but color noise in generated images is insufficiently reduced
Solution Approach 1:
The patent segments the pixel array into distinct functional groups: first pixel groups (RGB pixels) dedicated to generating resolution data and second pixel groups (W pixels) dedicated to generating color data. This segmentation allows each pixel type to optimize its specific function, with RGB pixels providing spatial resolution information and W pixels providing accurate color information, thereby reducing color noise while maintaining high sensitivity.
Solution Approach 2:
The patent introduces an intermediary processing stage that separates resolution data and color data into distinct processing streams. Resolution data from RGB pixels and color data from W pixels are processed independently through different computational paths before being combined, allowing optimized noise reduction algorithms to operate on each data type separately and effectively reduce color noise.
2Measurement precision
If up-conversion processing is performed to enhance image resolution, then image resolution is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary separation of resolution data and color data at the pixel readout stage, organizing them into distinct data streams before processing. This preliminary organization simplifies subsequent up-conversion processing by providing structured input data, reducing the computational complexity compared to processing mixed pixel data.
Solution Approach 2:
The patent applies up-conversion processing that increases the dimensional resolution of the image data. By processing resolution data and color data through different computational dimensions and then combining them, the system achieves enhanced image resolution while managing processing complexity through structured multi-dimensional processing.
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 reduces color noise and maintains high image resolution, while also ensuring compatibility with existing image processing units, thereby generating images with improved signal-to-noise ratio and reduced false colors.
Implementation Method 1
each of the photoelectric conversion units included in the first pixel group and each of the photoelectric conversion units included in the second pixel group have mutually different wavelength bands of lights to be photoelectrically converted
Data Source
AI summary
Resolution data is generated by using signals output by a first pixel group. Color data is generated by using signals output by a second pixel group. The resolution data is combined with the color data to generate first data. Up-conversion processing is performed on the first data to generate second data, and mosaic processing is performed on the second data to generate data of a predetermined array.