Omnidirectional Image Object Removal via Background Interpolation
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Solution Overview
Problem
Omnidirectional imaging systems often capture objects unintentionally, leading to the need for post-processing to remove these unwanted objects and generate natural, high-quality images.
Innovation Solution
An image processing device determines and removes processing-target objects from omnidirectional images through image post-processing, using a communication unit and processor to identify and interpolate or remove unintentionally imaged objects, thereby generating natural images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If omnidirectional imaging is used to capture wide field-of-view images, then the coverage and applicability are improved, but unintentionally imaged objects are introduced that require post-processing removal
Solution Approach 1:
The system performs preliminary action by detecting processing-target objects in the captured image before final image generation. The processor identifies objects that need to be removed (such as unintended subjects or obstacles) and marks them for removal, allowing the main image rendering process to proceed while scheduling separate processing for identified problematic objects.
Solution Approach 2:
The system extracts processing-target objects from the captured image by detecting their boundaries and separating them from the background. The processor identifies regions corresponding to objects to be removed, extracts these regions, and then fills the extracted areas with synthesized background information, effectively removing the unwanted objects from the final omnidirectional image.
2Manufacturing precision
If post-processing is performed to remove processing-target objects, then image quality is improved, but processing time and computational complexity increase
Solution Approach 1:
The system applies partial action by selectively processing only specific regions of the image that contain processing-target objects, rather than processing the entire image. The processor identifies and processes only the areas where objects need to be removed, leaving the rest of the image unchanged, thereby reducing overall processing time and computational resources required.
Solution Approach 2:
The system uses copying by synthesizing background information to replace removed objects. The processor creates copy pixels by referencing surrounding background areas and replicating their characteristics to fill the gaps left by removed objects, maintaining visual continuity without requiring complex reconstruction of the entire scene.
3Manufacturing precision
If processing-target objects are removed from the image, then natural image appearance is improved, but image completeness and information retention deteriorate
Solution Approach 1:
The system converts the harmful effect of removed objects into a benefit by using the removal process as an opportunity to enhance background visibility. By removing processing-target objects that obscure important background elements, the system actually improves the overall image quality and information content, allowing viewers to see background details that were previously hidden by unwanted objects.
Data Source
AI summary
The present disclosure relates to a method for removing an object to be processed from an image and a device for performing the method. A method for removing an object to be processed from an image can comprise the step of: an image processing device deciding an object to be processed in an image; and the image processing device performing image post-processing with respect to the object to be processed, wherein the object to be processed can be an object which is unintentionally captured.