3D Image Layer Processing With Neural Denoising and Alpha Compositing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Identifying layers of a three-dimensional image to generate a two-dimensional representation requires significant memory, time, or computing resources, which are not efficiently utilized in existing methods.
Innovation Solution
A neural denoiser with layer embeddings network is employed to partition samples into layers, apply unique filter kernels, and composite them using alpha blending, utilizing fully connected networks for efficient denoising and rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to identify layers of a three-dimensional image, then accurate layer identification can be achieved, but significant memory, time, and computing resources are consumed
Solution Approach 1:
The patent segments the three-dimensional image into multiple layers based on depth information and spatial coordinates. By dividing the 3D image space into discrete depth layers, the system can process each layer independently, reducing the computational complexity compared to processing the entire 3D volume as a single entity. This segmentation enables efficient memory management and parallel processing of layer data.
Solution Approach 2:
The patent introduces a depth dimension parameter to organize image data, transforming the processing approach from traditional 2D image processing to 3D spatial processing. By adding the depth dimension as an explicit parameter, the system can efficiently manage and process volumetric data through layer-based operations, improving both accuracy and resource utilization.
2Loss of information
If traditional methods are used to identify layers of a three-dimensional image, then complete image data can be processed, but excessive memory and time resources are required
Solution Approach 1:
The patent divides the complete 3D image data into multiple depth-based layers, allowing the system to process and store information in a structured manner. This segmentation preserves all image data while enabling selective processing of individual layers, reducing the time required to access and manipulate specific portions of the image without losing any information.
Solution Approach 2:
The patent performs preliminary organization of 3D image data into depth-sorted layers before processing. By pre-organizing the volumetric data according to depth coordinates, the system eliminates the need for repeated sorting and filtering operations during subsequent processing stages, significantly reducing processing time while maintaining data completeness.
Data Source
AI summary
Apparatuses, systems, and techniques to identify one or more layers of a three-dimensional graphical image to generate a two-dimensional representation. In at least one embodiment, one or more layers of a three-dimensional graphical image are identified to generate one or more two-dimensional representations.