3D Display Image Modification Logic for Non-Encoded Content
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Solution Overview
Problem
Existing 3D display systems fail to properly render images not encoded for 3D mode, resulting in distorted views when attempting to display them, as they lack the necessary encoding information to correctly present differing views to each eye, leading to unintended visual effects.
Innovation Solution
A display system that receives both encoded and non-encoded images, analyzes the non-encoded images to determine the required 3D display mode information, modifies them to match the encoding of the encoded images, and overlays or combines the modified images to create a proper 3D visualization, using components like image analysis units, image modification logic, and 3D display logic to ensure correct rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a 3D display system displays images not encoded for 3D mode, then the display can show any image content, but the image becomes distorted and produces unintended visual effects
Solution Approach 1:
The system performs preliminary analysis on the input image to detect whether it is encoded for 3D mode before display. This advance detection allows the system to prepare appropriate processing in advance, preventing distortion by identifying non-encoded images before they are rendered in 3D mode.
Solution Approach 2:
The system modifies image parameters dynamically based on the detected encoding state. When a non-encoded image is detected, the system changes the pixel arrangement parameters to create appropriate left-eye and right-eye views, transforming the image into proper 3D format while maintaining content integrity.
2Manufacturing precision
If the system analyzes and modifies non-encoded images to match encoded image format, then proper 3D display is achieved, but the processing time and system complexity increase
Solution Approach 1:
The system applies different processing treatments to different regions of the image based on local characteristics. The image analysis unit examines specific portions of the image to detect encoding patterns, and only modifies regions that require conversion, leaving already-encoded regions unchanged. This selective processing reduces overall system complexity while maintaining rendering accuracy.
Solution Approach 2:
The system includes self-detection capabilities where the image analysis unit automatically identifies whether an image is encoded for 3D mode without requiring external metadata or manual configuration. This self-service approach simplifies the system architecture by eliminating the need for separate encoding verification systems.
3Manufacturing precision
If the system converts non-encoded images to 3D format through pixel manipulation, then coherent 3D illusion is created, but processing speed decreases
Solution Approach 1:
The image conversion process is divided into separate functional segments: detection of encoding status, extraction of left-eye and right-eye views, and combination into 3D format. This segmentation allows each processing stage to be optimized independently and enables parallel processing of different image regions, improving overall processing speed while maintaining 3D visualization quality.
Data Source
AI summary
Modifying images for a 3-dimensional display mode includes receiving a third image encoded for a 3-dimensional display mode, receiving a first image not encoded for the 3-dimensional display mode, modifying the first image to generate a second image encoded for the 3-dimensional display mode, and displaying the third image and the second image in the 3-dimensional display mode.