Iterative Image Processing for Layered 3D Displays
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Solution Overview
Problem
Conventional methods for displaying three-dimensional images using stacked screens require high computational power and expensive hardware due to complex optimization calculations, making them inefficient and costly.
Innovation Solution
An image processing apparatus that iteratively generates internal data for multiple screen images using an input unit, initial solution generator, and iterative process controller, reducing calculation complexity and hardware requirements by employing a simple iterative process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optimization calculation methods are used to determine images for stacked screens, then depth representation beyond screen space is achieved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent segments the image determination process into multiple iterative rounds, where each round refines the screen images based on feedback from the previous round. This divides the complex optimization problem into manageable steps, reducing computational burden while maintaining depth representation accuracy.
Solution Approach 2:
The patent employs a dynamic iterative process where the image data on stacked screens is continuously updated and refined through multiple rounds of calculation. The process adapts based on termination conditions, allowing the system to balance between computational efficiency and depth representation precision.
2Measurement precision
If conventional optimization calculation methods are used to determine images for stacked screens, then depth representation beyond screen space is achieved, but hardware requirements increase due to need for high computing power
Solution Approach 1:
By segmenting the optimization calculation into iterative rounds with clear termination conditions, the patent reduces the computational burden on hardware. Each round performs limited calculations that can be completed with simpler processing units, eliminating the need for expensive high-performance computing hardware.
Solution Approach 2:
The patent uses a simplified iterative approach that copies and refines image data across multiple rounds rather than performing complex direct optimization. This copying and refinement strategy reduces computational complexity while maintaining the ability to represent depth beyond screen space.
3Device complexity
If iterative process with multiple rounds is used to generate screen images, then calculation complexity is reduced, but processing time increases due to multiple iterations
Solution Approach 1:
The patent implements feedback mechanisms within the iterative process, where each round evaluates termination conditions based on the results from the previous round. This feedback allows the system to terminate early when sufficient accuracy is achieved, balancing reduced calculation complexity with acceptable processing time.
Solution Approach 2:
The patent performs partial optimization through a limited number of iterative rounds rather than exhaustive optimization. By performing sufficient but not excessive iterations, the system achieves adequate depth representation with reduced computational complexity and acceptable processing time.
4Device complexity
If simple iterative process is used instead of complex optimization calculation, then hardware requirements are reduced, but image quality may deteriorate
Solution Approach 1:
The patent uses a dynamic iterative process that adapts to the input images and termination conditions, allowing the system to maintain image quality while using simpler hardware. The iterative refinement ensures that image quality is preserved through progressive improvement across multiple rounds.
Solution Approach 2:
The feedback mechanism in the iterative process monitors image quality and termination conditions, allowing the system to maintain adequate image quality even with simplified hardware. The feedback ensures that the iterative refinement continues until sufficient quality is achieved, preventing excessive quality deterioration.
Data Source
AI summary
An image processing apparatus includes: an initial solution generator that generates, from input images, as an initial solution, internal data of one or more screen images of a layered image, the layered image including multiple screen images consisting of the one or more screen images and one end image; an image generator that iterates a process of generating internal data of the multiple screen images; and a controller that, when a termination condition is satisfied, outputs, as data of the layered image, the finally generated internal data of the multiple screen images. The image generator generates internal data of the multiple screen images from the initial solution in a first round of the process, and then until the termination condition is satisfied, in each round of the process, generates new internal data of the multiple screen images from the internal data generated in the previous round of the process.