Abstract
When combining very different images which often contain complex objects and backgrounds, producing consistent compositions is a challenging problem requiring seamless image editing. In this paper, we propose a general approach, called object-aware image editing, to obtain consistency in structure, color, and texture in a unified way. Our approach improves upon previous gradient-domain composition in three ways. Firstly, we introduce an iterative optimization algorithm to minimize mismatches on the boundaries when the target region contains multiple objects of interest. Secondly, we propose a mixed-domain consistency metric for measuring gradients and colors, and formulate composition as a unified minimization problem that can be solved with a sparse linear system. In particular, we encode texture consistency using a patch-based approach without searching and matching. Thirdly, we adopt an object-aware approach to separately manipulate the guidance gradient fields for objects of interest and backgrounds of interest, which facilitates a variety of seamless image editing applications. Our unified method outperforms previous state-of-the-art methods in preserving global texture consistency in addition to local structure continuity.
Highlights
Seamless image editing has been an active research field in recent years
Since input images often contain multiple objects with differently textured backgrounds, a natural-looking editing result should meet the expectations of human visual perception [5] and preserve local structure continuity within boundaries and consistent color and texture transitions between source and target images
Results generated by the four methods Poisson image editing (PIE), drag-and-drop pasting (DDP), error-tolerant image composition (ETIC), and image melding (IM) all have artifacts in the background region, e.g., around the object boundaries
Summary
Seamless image editing has been an active research field in recent years It is widely applied in panorama mosaicing [1], photo composition [2, 3], manipulating large collections of photos [4], and so on. Seamless image editing involves combining source regions with target images in a visually natural way. Since input images often contain multiple objects with differently textured backgrounds, a natural-looking editing result should meet the expectations of human visual perception [5] and preserve local structure continuity within boundaries and consistent color and texture transitions between source and target images. When combining images with very different structures and textures, a successful image editing algorithm should preserve the following properties, to produce results in agreement with our visual perception: 1) Local structure continuity. When the input images have very different textures, the process should take into account gradients and colors to preserve texture consistency
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