Confocal Imaging for Visual Prostheses
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Solution Overview
Problem
Current visual prostheses face limitations in providing effective visual information to vision-impaired individuals due to low resolution, limited dynamic range, and cluttered backgrounds, making it difficult for users to navigate and recognize objects in their environment.
Innovation Solution
The system employs confocal imaging techniques to generate images focused on specific distances, allowing for the suppression of out-of-plane objects and background clutter, transforming these images into compressed formats suitable for retinal implants, using light-field cameras and image processing to enhance object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If confocal imaging is used to suppress background clutter, then object recognition is improved, but device complexity increases
Solution Approach 1:
The imaging system divides the visual scene into multiple focal planes at different distances from the user. By segmenting the depth space and selectively focusing on specific planes, the system suppresses background clutter while enhancing foreground objects, thereby improving object recognition without requiring complex post-processing
Solution Approach 2:
The system transitions from conventional 2D imaging to 3D confocal imaging by adding the depth dimension. Light-field cameras capture four-dimensional light field data (x, y, angular x, angular y), enabling selective focusing at different distances and effective clutter suppression through depth-based segmentation
2Adaptability or versatility
If image compression is applied to reduce data for retinal implants, then device adaptability is improved, but information loss increases
Solution Approach 1:
The system applies different processing qualities to different regions of the image based on their importance. Critical features such as object edges and high-contrast boundaries are preserved with higher fidelity, while less important regions undergo greater compression, optimizing the balance between data reduction and information retention for retinal implant compatibility
3Measurement precision
If confocal imaging with multiple focal planes is implemented, then object recognition is improved, but processing time increases
Solution Approach 1:
The system performs preliminary processing by capturing the complete light field data in a single shot, encoding depth and focus information directly in the captured image. This preliminary encoding eliminates the need for time-consuming sequential focal plane acquisition and enables rapid processing of multiple focal planes through computational algorithms
Data Source
AI summary
The disclosure features systems and methods for providing information to a user about the user's environment. The systems feature a detection apparatus configured to obtain image information about the environment, where the image information corresponds to information at multiple distances relative to a position of the user within the environment, and an electronic processor configured to obtain focal plane distance information defining a set of one or more distance values relative to the position of the user within the environment, construct one or more confocal images of the environment from the image information and the set of one or more distance values, wherein each of the one or more confocal images corresponds to a different distance value and includes a set of pixels, and transform the one or more confocal images to form one or more representative images having fewer pixels and a lower dynamic range.