On active contour models and balloons
CVGIP: Image Understanding
Computing occluding and transparent motions
International Journal of Computer Vision
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer graphics in medicine: from visualization to surgery simulation
ACM SIGGRAPH Computer Graphics
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fragment-based image completion
ACM SIGGRAPH 2003 Papers
MCMC for joint noise reduction and missing data treatment indegraded video
IEEE Transactions on Signal Processing
A topology preserving level set method for geometric deformable models
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Recently the method restoring an old picture using the local differential equation on the basis of the geometric measure is proposed. It is necessary to restore an old film and a medical image with noise as well as an old picture. So we extend the method applying for the two dimentional image such as a picture to the three dimensional image such as a time sequence image and a medical image. It is necessary to obtain an object boundary from the original image in order to generate a composite image of good quality, which is difficult to distinguish from the original image. If an object boundary can not be detected, it is difficult to remove the object. In this study, we propose a method for detecting an object boundary and removing it and inpainting its image in a manner that makes it difficult to distinguish from the original image. We extend the image partition method based on the level set method to the method applying for the movie and the medical image to detect an object boundary. We demonstrate its effectiveness by removing a terop from a movie and a tumor from a three dimensional medical image.