Posts 51-56 of 56
Selective Multi-Source Total Variation Image Restoration
We show that fusing multiple noisy images under a total variation penalty improves reconstruction. This idea can be selectively applied to individual pixels of each source image in the case of corrupted sections of images. View on Google Scholar.
Low Rank Sequential Subspace Clustering
We show that forcing the affinity matrix of SpatSC to be low-rank improves performance. View on Google Scholar.
Affinity Pansharpening and Image Fusion
We show that the pixel affinity from a high resolution image can be used to enhance low resolution images of the same scene. This technique is general enough to support fusion between any image types. View on Google Scholar.
Subspace Clustering for Sequential Data
We show that subspace clustering on sequential data can be dramatically improved by incorporating spatial constraints. View on Google Scholar.
Image Matting for Sparse User Input by Iterative Refinement
We show that iteratively refining an alpha matte can lead to impressive results with very sparse labels. View on Google Scholar.
Natural Image Matting with Total Variation Regularisation
We show that total variation regularisation improves alpha mattes. View on Google Scholar.
Posts 51-56 of 56