Transient Object Removal via Common Pixel Inference
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Solution Overview
Problem
Users often face difficulties in capturing and sharing unobstructed images of objects of interest due to transient objects obstructing the view, making it challenging to store and share clear, clutter-free images.
Innovation Solution
A computer-implemented method that receives a plurality of images, determines the most common pixel values to infer background pixels, and generates a composition by replacing foreground pixels with background pixels, thereby removing transient objects and creating an unobstructed image through alignment, normalization, smoothing, and blending algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple images are captured to remove transient objects, then the quality of the final unobstructed image is improved, but the complexity of the image processing system increases
Solution Approach 1:
The image processing is segmented into distinct stages: receiving multiple images, determining most common pixel values, generating compositions, and replacing foreground pixels with background pixels. This segmentation allows each stage to be optimized independently while maintaining overall system manageability despite the complexity of processing multiple images.
Solution Approach 2:
The system creates multiple copies of the same scene from different time points (multiple images) and processes them to extract the common background elements. By working with copies rather than the original single image, the system can synthesize an unobstructed view without permanently altering any single source image.
2Measurement precision
If manual efforts are used to remove transient objects, then the precision of object removal is improved, but the time consumption increases
Solution Approach 1:
The system performs automatic object removal without requiring manual user intervention. The computer-implemented method autonomously receives multiple images, determines common pixel values, generates compositions, and replaces foreground pixels with background pixels, eliminating the need for manual editing while maintaining high precision in removing transient objects.
Solution Approach 2:
The manual mechanical process of editing images is replaced with an automated computer-based image processing system. The system uses algorithms to automatically identify and remove transient objects by comparing multiple images and synthesizing a final unobstructed image, substituting human manual effort with automated computational processing.
3Speed
If simple image processing algorithms are used, then the processing speed is improved, but the quality of the synthesized image deteriorates
Solution Approach 1:
The system processes only the necessary portions of the images to achieve the desired result. By focusing on determining the most common pixel values at each position and generating compositions selectively, the system avoids unnecessary processing steps while maintaining high image quality in the final synthesized output.
Data Source
AI summary
In one aspect, the present subject matter is directed to a computer-implemented method for removing transient objects to synthesize an unobstructed image. The method includes receiving a plurality of images from a user. A most common value at a same pixel of each image is determined to infer pixels associated with a background of the images. A composition is generated from the received images, wherein the composition includes one of the pixels associated with the background of the images in place of a pixel associated with a foreground of at least one of the images.