Hologram Generation via Retina Coordinate Transformation
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Solution Overview
Problem
Conventional polygon computer-generated holograms (CGHs) suffer from dark-line defects in holographic 3D images due to abrupt wavefront changes between triangular apertures, leading to decreased image clarity.
Innovation Solution
A hologram generation apparatus and method that transforms 3D objects into polygonal facets, generates light wave analysis data, and applies an inverse Fresnel Transform to eliminate dark-line defects by optimizing light wave distribution between the object and retina spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional polygon CGH method is used to generate holographic 3D images, then the imaging process is simple and straightforward, but dark-line defects appear due to abrupt wavefront changes between triangular apertures
Solution Approach 1:
The patent applies preliminary action by performing coordinate transformation from object space to retina space before generating the CGH. This preliminary transformation of the polygonal facets into the retina coordinate system allows the subsequent hologram generation to proceed without dark-line defects, as the wavefront continuity is established in advance through the coordinate transformation step.
2Ease of manufacture
If triangle apertures are used in polygon CGH, then the 3D object can be represented as polygonal facets, but abrupt wavefront changes occur between triangles causing dark-line defects
Solution Approach 1:
The patent applies parameter changes by transforming the coordinate system parameters from object space to retina space. This change in coordinate parameters fundamentally alters how the polygonal facets are represented, converting the abrupt wavefront changes between triangles into continuous wavefront transitions in the retina coordinate system, thereby eliminating dark-line defects while preserving the simplicity of polygonal modeling.
3Productivity
If direct CGH generation from polygonal facets is performed, then the process is efficient, but image clarity decreases due to dark-line defects
Solution Approach 1:
The patent introduces an intermediary coordinate transformation step that acts as a mediator between the polygonal facet representation and the final CGH generation. By transforming coordinates from object space to retina space as an intermediate processing stage, the method maintains computational efficiency while significantly improving image clarity by eliminating dark-line defects through the coordinate mediation.
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 effectively removes dark-line defects from holographic images, enhancing image clarity and quality by transforming light wave data through normal/reference coordinates and inverse Fresnel Transform processes.
Implementation Method 1
an inverse Fresnel Transform to eliminate dark-line defects by optimizing light wave distribution between the object and retina spaces
Implementation Method 2
holography technique uses a principle of recording and reconstructing interference signals obtained when light reflected from an object (object beam) and light with coherency (reference beam) intersect with each other
Data Source
AI summary
A hologram generation apparatus is based on a hologram imaging system which includes an object space where an object is situated and a retina space or region where an image is formed within an eyeball of an observer. The hologram generation apparatus includes a modeling unit for generating first graphic data by transforming a 3D image of a 3D object to a set of polygonal facets; a data transformation unit for generating second graphic data by transforming the first graphic data from the modeling unit to normal/reference coordinates in the retina region; a hologram generation unit for generating a first computer generated hologram (CGH1), which is light wave analysis data for the second graphic data; and a hologram transformation unit for transforming the first computer generated hologram (CGH1) in the retina region to a second computer generated hologram (CGH2) in the object space.