Coded Aperture Ghost Image Distance Estimation
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Solution Overview
Problem
Existing methods for determining the distance to objects based on images captured by image capture devices are complex, unreliable, and require high computational resources, especially when dealing with depth contrasts and similar intensities, leading to suboptimal depth data and increased complexity.
Innovation Solution
An apparatus and system using a coded aperture with a low number of openings in an image capture device, positioned out of focus, generates ghost images that allow for low-complexity detection of image objects based on optical characteristics, enabling distance determination from a single image without complex image processing, suitable for low computational resources and real-time applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional lens apertures are used to capture images for depth determination, then the system is simple in structure, but the defocus blur introduced is mathematically irreversible and not discriminative to depth, resulting in unreliable depth data
Solution Approach 1:
The aperture is segmented into multiple discrete openings (e.g., 3-7 openings) arranged in a specific pattern rather than using a conventional continuous aperture. This segmentation creates distinct ghost images for different depth planes, making depth information discriminative and reliable while maintaining relatively simple device structure
Solution Approach 2:
The coded aperture creates multiple copies (ghost images) of the scene at different positions in the image plane, each corresponding to a specific depth range. By analyzing the positions and intensities of these copied images, reliable depth information can be extracted without requiring complex computational processing
2Measurement precision
If a coded aperture with broadband pattern is used to shape defocus blur for depth recovery, then depth information can be obtained, but the system requires high computational resources and complex processing
Solution Approach 1:
The patent changes the aperture parameters from a conventional continuous opening to a coded pattern with specific geometric characteristics (e.g., radial lines, concentric circles). This parameter change transforms the defocus blur from an irreversible mathematical problem into a pattern recognition problem that can be solved with simple image processing algorithms
Solution Approach 2:
The coded aperture creates depth-dependent intensity variations and spatial patterns in the captured image, analogous to color changes. Different depth planes produce distinct intensity distributions and ghost image patterns that can be easily differentiated through simple thresholding and pattern matching operations
3Loss of information
If the image sensor is positioned in the focus plane for the scene object, then the image is sharp, but no defocus blur is generated and depth information cannot be determined
Solution Approach 1:
The system dynamically utilizes the defocus blur effect by intentionally positioning the image sensor out of the focus plane for the scene object. The coded aperture is designed to create structured ghost images even in this out-of-focus condition, transforming what is normally a degradation (blur) into a useful signal for depth determination
4Reliability
If complex image processing is performed to separate contributions from overlapping defocus blurring kernels, then depth information can be recovered, but the processing time and computational resources increase significantly
Solution Approach 1:
The patent extracts only the essential depth-related features from the image by detecting the positions of ghost images produced by the coded aperture. Instead of performing complex processing to separate overlapping blurring kernels, the method directly extracts depth information from the spatial distribution of ghost images, significantly reducing processing time while maintaining reliability
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 facilitates accurate and efficient distance determination to objects, particularly humans, with reduced computational requirements, enabling reliable detection of pupils and head orientation, and is suitable for use in various scenarios, including mobile devices and autostereoscopic displays.
Implementation Method 1
a coded aperture having a broadband pattern and a statistical model of images to recover depth and reconstruct an all-focus image of the scene
Implementation Method 2
an image sensor of an image capture device having a coded aperture
Data Source
AI summary
A system for determining a distance to an object comprises an image capture device (101) which has a coded aperture and an image sensor which is positioned out of a focus plane of the coded aperture. A receiver (103) receives an image of a scene from the image sensor and a detector (105) detects at least two image objects of the image corresponding to ghost images of the object resulting from different openings of the coded aperture in response to an optical characteristic of the object. A distance estimator (107) then determines a distance to the object in response to a displacement in the image of the at least two image objects. The distance may be to a person and the image may be a bright pupil image wherein pupils are enhanced by reflection of light by the retina. The image may be compensated by a dark pupil image of the scene.