Local Color Range Selection Using Spatial and Range Masks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional digital image editing tools require a complex, multi-step workflow for local adjustments, often resulting in inaccurate and destructive edits due to irregular spatial boundaries, making it difficult to apply precise adjustments to images with complex regions like those with red leaves and foliage.
Innovation Solution
The method involves generating separate spatial and range masks, where the spatial mask defines the region for adjustment and the range mask specifies the color and tone ranges to adjust, allowing for weighted adjustments based on both masks to achieve precise edits without altering the original image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single mask is used to define regions for local adjustments, then the editing process is simple, but the accuracy of adjustments to complex regions like red leaves is poor
Solution Approach 1:
The patent divides the mask into two separate components: a spatial mask for defining the region and a range mask for specifying color/tone parameters. This segmentation allows each mask to be optimized independently, with the spatial mask handling region definition and the range mask handling color range selection, thereby improving accuracy without increasing overall complexity
Solution Approach 2:
The patent adds a new dimension to mask definition by introducing range masks that operate in color space rather than just spatial space. This allows adjustments to be made based on color ranges (e.g., red leaves vs. red building) in addition to spatial regions, enabling precise targeting of complex regions
2Reliability
If conventional mask tools are used for local adjustments, then the workflow is straightforward, but the edits are destructive and cannot be undone
Solution Approach 1:
The patent creates a non-destructive copy of the original image data by storing adjustments as separate mask layers that can be applied without modifying the original. The spatial mask and range mask serve as independent copies that define the adjustment region and parameters, allowing the original image to remain intact while enabling reversible edits
3Productivity
If manual brush tools are used to select regions, then precise control is achieved, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent implements automated region selection by allowing users to define coarse regions (e.g., using a simple brush or gradient tool) and then having the system automatically refine the selection using range masks that identify pixels matching specific color and tone criteria. This self-service approach eliminates the need for manual pixel-by-pixel selection while maintaining high precision
4Measurement precision
If adjustments are applied to all pixels in a region, then the editing process is simple, but the ability to differentiate between similar colors (e.g., red leaves vs. red building) is lost
Solution Approach 1:
The patent applies local quality by allowing different adjustment parameters to be applied to different pixels within the same spatial region based on their color and tone properties. The range mask enables pixels with similar spatial locations but different color characteristics (e.g., red leaves vs. red building) to be treated differently, with adjustments applied selectively based on the specified color range
Data Source
AI summary
Techniques of editing images using a digital image editing tool involve defining a local adjustment that includes, as separate masks, a spatial mask and a range mask. The spatial mask specifies a region of the image to be adjusted and the range mask specifies ranges of colors and tones to be adjusted independent of the region specified by the spatial mask. In applying these masks, when a user changes a setting in the digital image editing tool, the digital image editing tool weights the effect of the setting according to the values of the spatial mask and the range mask for each pixel of the image.