Selective Image Editing via Local Area Restoration
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Solution Overview
Problem
Current image editing tools require users to manually select and adjust pixel characteristics, which can be time-consuming and inefficient, especially when applying complex edits to specific areas of an image.
Innovation Solution
A computer-implemented method and system that allows users to select a selective editing tool to apply previous edit operations to specific local areas of an image, restoring the image to a previous state and enabling the application of edit operations using intuitive tools like brush, gradient, or control point tools, allowing for efficient and precise editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual pixel selection and adjustment is used for image editing, then editing precision can be achieved, but editing time and effort increase significantly
Solution Approach 1:
The system automatically identifies and selects relevant image regions based on edit operation parameters, eliminating the need for users to manually select pixels. The algorithm autonomously determines which areas should be affected by the edit operation, allowing users to simply specify the desired edit effect.
Solution Approach 2:
The system pre-calculates and identifies candidate regions that would be affected by potential edit operations before the user finalizes their selection. This preliminary region identification is based on analyzing image characteristics and the intended edit operation, so when the user applies the edit, the affected areas are already determined and ready for processing.
2Productivity
If complex edit operations are applied to entire images, then comprehensive editing coverage is achieved, but system resource consumption increases
Solution Approach 1:
Instead of applying edit operations uniformly across the entire image, the system identifies specific local regions that should be affected by the edit based on image content analysis and user intent. Different parts of the image receive different treatment - some regions are edited while others remain unchanged, optimizing resource usage by processing only necessary areas.
Solution Approach 2:
The image is automatically segmented into multiple regions with different characteristics, and edit operations are selectively applied to relevant segments. This segmentation allows the system to process only the portions of the image that require editing, rather than applying computationally intensive operations to the entire image data set.
3Productivity
If selective editing tools are introduced to apply edits to local areas, then editing efficiency improves, but tool complexity increases
Solution Approach 1:
The system uses template-based approaches where common selective editing patterns are pre-defined and stored as templates. Users can select from these pre-configured templates rather than manually configuring complex selective editing parameters, thus maintaining simplicity while achieving sophisticated selective editing results.
Solution Approach 2:
The selective editing tool is designed to handle multiple types of edit operations (brightness adjustment, color correction, filtering, etc.) through a single unified interface. Rather than providing separate complex tools for each editing task, the system offers one versatile tool that adapts to different editing needs, reducing the overall complexity of the editing toolbox.
Data Source
AI summary
Implementations relate to editing images with selective editing tools. In some implementations, a computer-implemented method for an image editing program causes a display of an image and receives user input from a user to the image editing program, the user input indicative of selection of a selective editing tool. The method restores the image to a previous state in which a first modification to one or more pixel values of the image is omitted, where the first modification resulted from previous application of a first edit operation to the image. The method applies a second edit operation to one or more local areas of the image as indicated by selection of the selective editing tool by the user input, and the applying causes a second modification to the image.