Selective Pixel Binning for Depth Image Accuracy
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Solution Overview
Problem
The accuracy of depth images acquired by sensors is compromised when the intensity of reflected light is insufficient due to small pixel size or large object distances, leading to reduced image quality.
Innovation Solution
A pixel binning apparatus that determines the output level of each pixel and selectively performs binning based on this level to increase accuracy, preventing edge blurring and maintaining image resolution by excluding pixels identified as edges through color information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel size is increased to improve depth image accuracy, then measurement precision improves, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent merges multiple pixels into a single pixel group through binning, where pixels are selectively combined based on output level thresholds. This allows the system to achieve the light-collecting advantage of larger pixels while maintaining the original pixel array structure, thus improving depth image accuracy without physically increasing pixel size or complicating sensor manufacturing.
Solution Approach 2:
The patent implements dynamic pixel binning where the binning configuration is not fixed but adaptively adjusted based on output levels of pixels. The system dynamically determines which pixels to bin together and which to keep separate, allowing flexible optimization of depth image accuracy for different imaging conditions without requiring a physically complex reconfigurable sensor structure.
2Measurement precision
If pixel binning is performed to increase light collection, then measurement precision improves, but image resolution deteriorates
Solution Approach 1:
The patent applies different binning strategies to different regions of the image based on local characteristics. High-output pixels that contribute to image quality are kept separate, while low-output pixels are binned to improve signal strength. This local differentiation allows the system to improve depth image accuracy through binning while preserving image resolution in critical regions.
Solution Approach 2:
The patent performs partial binning rather than complete binning of all pixels. By selectively binning only certain pixels based on their output levels and excluding edge pixels from binning, the system achieves improved light collection and depth accuracy for relevant regions while maintaining resolution in edge and high-quality regions, thus avoiding the resolution loss that would result from full binning.
3Measurement precision
If pixel binning is performed to improve signal strength, then measurement precision improves, but edge detail accuracy deteriorates due to blurring
Solution Approach 1:
The patent extracts and excludes edge pixels from the binning process. By identifying pixels located at object boundaries through color information and excluding them from binning operations, the system prevents edge blurring while still applying binning to interior pixels to improve signal strength and depth accuracy. This separation of edge and non-edge pixel processing resolves the contradiction between signal enhancement and edge detail preservation.
4Illumination intensity
If pixel size is increased to improve light collection, then illumination intensity sensitivity improves, but area occupied by each pixel increases
Solution Approach 1:
The patent combines multiple small pixels into functional pixel groups through binning, effectively creating larger light-collecting units without physically increasing the area of individual pixels. The sensor maintains its original compact pixel array layout, but the binning operation merges signals from multiple pixels to achieve the light collection capability of larger pixels, thus improving reflected light sensitivity without increasing pixel area.
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
The solution enhances the accuracy of depth images by increasing the quantity of electrons detected, thereby improving image quality without reducing resolution, even under low light conditions.
Implementation Method 1
A sensor to acquire a depth image receives light reflected from an object
Data Source
AI summary
An output level of a pixel is determined using a reflected light reflected against an object. Pixel binning is selectively performed according to the output level of the pixel.