Electronic Device Image Processing Non-Stationary Object Removal
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Solution Overview
Problem
Existing image processing technologies fail to effectively remove non-stationary objects from a sequence of images captured at different times, limiting the ability to create composite images without unwanted moving subjects.
Innovation Solution
An electronic device and method that detects non-stationary objects in a sequence of images, allows users to select a frame region containing these objects, and replaces the image data in that region with data from another image with low similarity, thereby removing the objects from the final composite image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If image data from consecutively captured images is used to create composite images, then the ability to capture moments on notice is improved, but non-stationary objects cannot be effectively removed from the composite image
Solution Approach 1:
The image is divided into multiple regions, with stationary regions being composite-ed from multiple frames and non-stationary regions being excluded. The processor identifies region types based on temporal consistency and selectively processes different regions differently, allowing efficient composite image creation while maintaining content accuracy.
Solution Approach 2:
Different processing strategies are applied to different regions of the image. Stationary regions undergo composite editing to capture momentous events, while non-stationary regions are identified and excluded from compositing. This localized approach ensures that each region is processed according to its characteristics, resolving the contradiction between efficiency and accuracy.
2Adaptability or versatility
If automated detection of non-stationary objects is implemented, then image processing capability is improved, but device complexity increases
Solution Approach 1:
The system dynamically adjusts processing based on detected motion characteristics. Rather than using a fixed complex algorithm for all images, the processor adapts its behavior based on the presence and characteristics of non-stationary objects in each specific image sequence, achieving high adaptability with manageable complexity.
Solution Approach 2:
The image processing system automatically detects and handles non-stationary objects without requiring manual intervention or complex external processing systems. The device performs self-analysis of image sequences, automatically identifying region types and applying appropriate processing, thereby enhancing capability while keeping the system relatively simple.
Data Source
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AI summary
A method and apparatus for image processing includes receiving images, detecting non-stationary objects in the images, displaying a first image that includes a non-stationary object, selecting a frame region including the non-stationary object in the first image, selecting a second image based on a low similarity with the first image, and replacing image data in the frame region of the first image with image data represented in the frame region of the second image.