Light Field Calibration via Ray Parameter Standardization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current light-field technologies lack a standard for the acquisition and transmission of multi-dimensional information, leading to proprietary file formats and limitations in interactivity and post-processing capabilities compared to 2D or 3D imaging.
Innovation Solution
A system and method for representing and processing 4D light-field data using parameters that define rays in an optical acquisition system, including coordinates and direction cosines, to trace rays in both image and object spaces, and a light field imaging device with micro lenses and a calibration mechanism to improve signal processing and image mixing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proprietary file formats are used for light-field data acquisition, then device-specific optimization is achieved, but interoperability and standardization are compromised
Solution Approach 1:
The patent applies universality by creating a standardized file format that can store light-field data from different acquisition devices (plenoptic cameras, camera arrays, focal plane sweeping systems) in a unified structure. The format supports multiple data representations (raw images, sub-aperture images, epipolar images) and includes calibration data for various optical configurations, enabling interoperability across diverse light-field capture systems while maintaining device-specific optimization capabilities
2Adaptability or versatility
If 4D light-field data acquisition is implemented, then post-processing capabilities are enhanced, but data complexity and processing requirements increase
Solution Approach 1:
The patent applies segmentation by dividing the complex 4D light-field data into distinct organizational structures within the file format. It separates raw captured data from processed representations (sub-aperture images, epipolar images), stores calibration data independently, and organizes metadata in structured fields. This segmentation allows selective processing of different data components, reducing overall system complexity while maintaining enhanced post-processing capabilities
Solution Approach 2:
The patent manages data complexity by transforming 4D light-field data into different representational dimensions. It provides multiple viewing angles through sub-aperture images and enables refocusing at different depths through epipolar image stacks. The standardized format stores these multi-dimensional representations efficiently, allowing complex light-field information to be accessed and processed in simplified 2D image formats when needed
3Adaptability or versatility
If calibration data is stored in standardized format, then data interchangeability is improved, but storage requirements increase
Solution Approach 1:
The patent applies parameter changes by providing multiple levels of calibration data precision and optional storage. The file format supports storing only essential calibration parameters (pupil center coordinates, lens characteristics) or more comprehensive calibration datasets depending on application needs. This selective parameter storage reduces file size while maintaining data interchangeability across different light-field processing applications
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
Enables improved de-multiplexing, de-mosaicking, and refocusing capabilities by establishing a correspondence between sensor pixels and object space, enhancing the rendering and interactivity of light-field images.
Implementation Method 1
the main lens 101 receives light from an object (not shown on the figure) in an object field of the main lens 101 and passes the light through an image field of the main lens 101
Implementation Method 2
a plenoptic camera is able to acquire 4D light-field data. Details of the architecture of a plenoptic camera are provided in Figure 1A. Figure 1A is a diagram schematically representing a plenoptic camera 100. The plenoptic camera 100 comprises a main lens 101, a microlens array 102 comprising a plurality of micro-lenses 103 arranged in a two-dimensional array and an image sensor 104
Data Source
Figure 1A~1B
Figure 2~3
Figure 4~5
AI summary
There are several types of plenoptic devices and camera arrays available on the market, and all these light field acquisition devices have their proprietary file format. However, there is no standard supporting the acquisition and transmission of multi-dimensional information. It is interesting to obtain information related to a correspondence between pixels of a sensor of said optical acquisition system and an object space of said optical acquisition system. Indeed, knowing which portion of the object space of an optical acquisition system a pixel belonging to the sensor of said optical acquisition system is sensing enables the improvement of signal processing operations. The notion of pixel beam, which represents a volume occupied by a set of rays of light in an object space of an optical system of a camera along with a compact format for storing such information is thus introduce.