Sky Replacement Preset Loading with Segmented Resolution
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Solution Overview
Problem
Current image editing techniques for replacing regions, such as skies, in images are time-consuming and computationally intensive, often resulting in inaccurate segmentations and unnatural composite images due to variations in appearance and complex boundaries with other objects.
Innovation Solution
An image editing system that stores thumbnails, region location information, and metadata for preset images, allowing for quick selection and loading of high-resolution images to generate composite images with automatic segmentation and color harmonization, using a layer structure for non-destructive editing and minimizing halo and fringing artefacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual segmentation is used to identify sky and foreground regions, then users can control the segmentation process, but the process becomes time-consuming and tedious
Solution Approach 1:
The system performs preliminary automated segmentation to generate initial sky and foreground masks before user interaction. This preliminary action provides a head start, reducing the time users need to spend on manual segmentation while maintaining control over the final result.
Solution Approach 2:
The system enables users to refine segmentation by simply brushing over regions they want to adjust, rather than requiring complete manual segmentation. The system automatically processes these brush strokes to update the masks, making the user serve themselves with minimal effort.
2Manufacturing precision
If high-resolution preset images are loaded for replacement, then image quality is improved, but computational intensity and loading time increase
Solution Approach 1:
The system segments preset images into multiple resolution levels (thumbnail, preview, and full resolution). Users first interact with low-resolution thumbnails for selection, then progress to medium-resolution previews for evaluation, and finally load full-resolution images only when needed for the final composite. This segmentation of resolution levels reduces overall computational intensity and memory usage.
Solution Approach 2:
The system loads and processes only the necessary portions of high-resolution images based on user selection and preview needs. Instead of loading all preset images at full resolution simultaneously, it selectively loads partial content at appropriate resolution levels, reducing computational overhead while maintaining image quality where needed.
3Measurement precision
If multiple preset images are stored with full resolution data, then selection quality is improved, but memory usage and loading speed deteriorate
Solution Approach 1:
The system segments preset image data into multiple resolution levels stored separately: thumbnails for quick browsing and selection, previews for detailed evaluation, and full-resolution images for final use. This segmentation allows rapid loading of thumbnail data for selection while maintaining the option to load higher resolution data only when needed, improving both selection accuracy and loading speed.
Solution Approach 2:
The system employs periodic or on-demand loading of higher resolution data. Thumbnails are loaded initially for selection, and only when a user selects a preset does the system periodically load the corresponding full-resolution image data. This periodic loading pattern improves initial loading speed while maintaining selection accuracy.
4Productivity
If automated segmentation is used for sky replacement, then processing speed is improved, but segmentation accuracy deteriorates due to variations in appearance and complex boundaries
Solution Approach 1:
The system performs preliminary automated segmentation to generate initial masks, but then requires user confirmation and refinement. This preliminary automated action provides a fast starting point, while the subsequent user refinement step corrects inaccuracies caused by variations in sky appearance and complex boundaries with trees and other objects.
Solution Approach 2:
The system incorporates feedback mechanisms where user corrections to automated segmentation masks are processed and used to refine future segmentation results. The feedback loop allows the system to learn from user corrections, improving segmentation accuracy over time while maintaining fast automated processing for initial mask generation.
Data Source
AI summary
Systems and methods for image editing are described. Embodiments of the present disclosure provide an image editing system for performing image object replacement or image region replacement (e.g., an image editing system for replacing an object or region of an image with an object or region from another image). For example, the image editing system may replace a sky portion of an image with a more desirable sky portion from a different replacement image. According to some embodiments described herein, thumbnails, region location information, and image metadata from multiple preset images can be stored together and loaded for presentation and selection of a preset image for replacing a region of an image. Once a preset image (e.g., an image with a replacement sky) is selected, a high-resolution version of the image can be loaded and used to generate a composite image.