Eliminating ghosting and exposure artifacts in image mosaics
By M. Uyttendaele, Ashley M. Eden, Richard Szeliski. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001
385 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/442a79321e5f1925ce6de1a7af28e05bf3731314
How researchers see this paper
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In Computer Vision and Pattern Recognition
- Luc Van Gool
- Ming-Hsuan Yang
- Dacheng Tao
- Kaiming He
- Xiaogang Wang
- Andrea Vedaldi
- Trevor Darrell
- Jitendra Malik
Citations in the corpus
- GP-GAN: Towards Realistic High-Resolution Image Blending (2017, background): “when there are significant differences between the source and target images. The other way is to make the transition as smooth as possible for hiding artifacts in the composite images. Alpha blending [33] is the simplest and fastest method, but it blurs the fine details when there are some registrat”
- Automatic Panoramic Image Stitching using Invariant Features (2007, background): “Another approach would be to automatically find optimal seam lines based on regions of difference between the images (Davis, 1998; Uyttendaele et al., 2001; Agarwala et al., 2004).”
- Seamless Image Stitching in the Gradient Domain (2004, methodology): “In case there are misalignments between the images[6], these methods leave artifacts in the mosaic such as double edges, as shown in Figure 2.”
- A Unified Framework for Street-View Panorama Stitching (2016, background): “In the last several decades, many image blending algorithms have been proposed to smooth the color differences along the seam lines, such as feathering [47], alpha blending [48], Laplacian pyramid blending [49], Poisson blending [50] and the gradient domain image blending approach [51].”
- Applications of Generative Adversarial Networks (GANs): An Updated Review (2019, background): “Alpha blending [110] is the simplest and fastest method, but it blurs the fine details when there are some registration errors or fast moving objects between the source images.”