Fragment-based image completion.pdf

Fragment-Based Image Completion Iddo Drori Daniel Cohen-Or Hezy Yeshurun School of Computer Science ? Tel Aviv University Figure 1: From left to right: the input image, and inverse matte that defines the removal of an element, the result of our completion, and the content of the completed region. Abstract We present a new method for completing missing parts caused by the removal of foreground or background elements from an image. Our goal is to synthesize a complete, visually plausible and coher- ent image. The visible parts of the image serve as a training set to infer the unknown parts. Our method iteratively approximates the unknown regions and composites adaptive image fragments into the image. Values of an inverse matte are used to compute a confidence map and a level set that direct an incremental traversal within the unknown area from high to low confidence. In each step, guided by a fast smooth approximation, an image fragment is selected from the most similar and frequent examples. As the selected fragments are composited, their likelihood increases along with the mean con- fidence of the image, until reaching a complete image. We demon- strate our method by completion of photographs and paintings. CR Categories: I.3.3 [Computer Graphics]: Picture/image generation—; I.4.1,3,5 [Image Processing and Computer Vision]: Sampling—,Enhancement,Reconstruction Keywords: image completion, example-based synthesis, digital matting, compositing ?e-mail: {idrori | dcor | hezy}@tau.ac.il 1 Introduction The removal of portions of an image is an important tool in photo- editing and film post-production. The unknown regions can be filled in by various interactive procedures such as clone brush strokes, and compositing processes. Such interactive tools require meticulous work driven by a professional skilled artist to complete the image seamlessly. Inpainting techniques restore and fix small- scale flaws in an image, like scratches or stains [Hirani and Totsuka 1996; Bertalmi