Dynamic Seam Carving for Content-Aware Image Resizing
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Solution Overview
Problem
Existing image resizing methods, such as cropping and scaling, do not account for the content of the image, leading to distortions and unnatural resizing results, especially when repeatedly removing or inserting seams in the same image area.
Innovation Solution
A content-aware digital image resizing system that uses a dynamic seam carving algorithm to select seams based on pixel importance values, applying a weighting function to distribute seams and avoid repeated selection from the same area, ensuring minimal distortion during resizing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If classical image resizing methods (cropping and scaling) are used, then the resizing process is simple and efficient, but the image content is distorted and important regions are lost
Solution Approach 1:
The patent applies local quality by computing importance values for different regions of the image, allowing different parts of the image to be treated differently during resizing. Important regions (with high importance values) are preserved while less important regions are removed through seam carving, thus maintaining image content quality while achieving efficient resizing.
Solution Approach 2:
The patent changes the parameter of pixel selection from uniform (classical methods) to variable (importance-based). By introducing importance values as a dynamic parameter that varies across the image, the system can adaptively select which pixels to remove, preserving important content while maintaining resizing efficiency.
2Productivity
If multiple seams are removed from the same image area, then the resizing target is achieved, but distortions become visible in the resized image
Solution Approach 1:
The patent implements feedback by using a weighting function that incorporates information from previously removed seams. The weighting function increases the importance values of pixels near previously removed seams, creating a feedback mechanism that prevents subsequent seams from being selected in the same areas, thus avoiding cumulative distortions while achieving the resizing target.
Solution Approach 2:
The patent applies preliminary anti-action by proactively increasing the importance values of pixels adjacent to previously removed seams through the weighting function. This preliminary adjustment prevents future seams from being selected in those areas, counteracting the potential for distortion before it can occur.
3Manufacturing precision
If a weighting function is applied to distribute seams, then distortions are reduced, but the computational complexity increases
Solution Approach 1:
The patent applies partial action by using a localized weighting function that only affects pixels in the vicinity of previously removed seams, rather than recalculating importance values for the entire image. This partial adjustment reduces computational complexity while still achieving distortion reduction through strategic seam distribution.
Data Source
AI summary
What is disclosed is a method for iterative seam selection in an image resizing system utilizing a seam carving technique. In one embodiment, an importance map is generated for a received source image. Seams are carved through the image from one edge to an opposite edge. An energy is computed for each seam based on pixel importance values. A distance is computed from each seam to a previously selected seam. A weighting for each seam is computed using a defined weighting function and the calculated seam distances. The weighting is applied to the energy of each seam produce a revised energy for each seam. A seam is selected based on the produced revised energy. The image is resized at a location of the selected seam. The process repeats until the image has been resized to a desired target output dimension. In such a manner, unnatural image resizing results are avoided.