Light Field Image Artifact Correction via User-Defined Depth Updates
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Solution Overview
Problem
Light field images often contain artifacts due to partially occluded regions and inaccuracies in depth and visibility information, which are challenging to correct using existing methods.
Innovation Solution
A method and system that allow users to identify and correct artifacts in light field images by generating updated depth and visibility estimates for specific regions, using a processor configured with an image processing application to re-render the image, incorporating user input for validation and iterative refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated depth estimation methods are used to process light field images, then processing speed and coverage are improved, but accuracy and reliability of depth information deteriorate due to artifacts in partially occluded regions
Solution Approach 1:
The patent segments the light field image into multiple regions of interest (ROIs) based on depth information. By dividing the image into distinct depth layers or planes, the system can process each region independently with appropriate depth estimation methods, improving overall accuracy while maintaining processing efficiency through parallelization of region processing.
Solution Approach 2:
The patent applies different depth estimation techniques or parameters to different regions of the image based on their specific characteristics. For example, regions with high occlusion may use different algorithms than regions with clear visibility, allowing each region to be processed with the most suitable method for its local conditions, thereby improving overall accuracy without sacrificing processing speed.
2Measurement precision
If iterative refinement methods are implemented to correct artifacts, then measurement precision of depth information is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary processing steps to identify and segment problematic regions before applying iterative refinement. By pre-processing the image to create depth maps and identify occluded regions in advance, the system can target iterative correction only to specific areas rather than processing the entire image repeatedly, significantly reducing computational time while maintaining precision.
Solution Approach 2:
The patent implements feedback mechanisms where depth estimation results are continuously validated and used to adjust subsequent processing steps. By using the output of one processing stage as input for refinement, the system achieves progressive improvement in accuracy without requiring complete reprocessing, thereby reducing overall computational time compared to traditional iterative methods.
3Reliability
If user interaction is added for artifact correction, then reliability of corrected images is improved, but ease of operation deteriorates due to additional user input requirements
Solution Approach 1:
The patent implements self-service functionality where the system automatically identifies and corrects common artifacts without requiring user intervention. By using automated detection algorithms that recognize typical occlusion patterns and depth estimation errors, the system can correct many artifacts independently, maintaining high reliability while minimizing the need for user input and preserving ease of operation.
Data Source
AI summary
Systems and methods for correction of user identified artifacts in light field images are disclosed. One embodiment of the invention is a method for correcting artifacts in a light field image rendered from a light field obtained by capturing a set of images from different viewpoints and initial depth estimates for pixels within the light field using a processor configured by an image processing application, where the method includes: receiving a user input indicating the location of an artifact within said light field image; selecting a region of the light field image containing the indicated artifact; generating updated depth estimates for pixels within the selected region; and re-rendering at least a portion of the light field image using the updated depth estimates for the pixels within the selected region.