Depth-Aware Patch-based Image Disocclusion for Virtual View Synthesis

If we now compare the results between a color and a patch lattice, with a patch-based ordering, the simplification effect is less strong and texture is much better preserved and

Denoising or restoration methods must preserve space-time discontinuities while minimizing the error between the unknown original noise-free image sequence and the denoised sequence..

In the official challenge of the MediaEval 2014 Retrieving Diverse Social Images task [1] a ranked list of location photos retrieved from Flickr (using text information) is given,

Abstract. This paper introduces recent methods for large scale image search. State-of-the-art methods build on the bag-of-features image rep- resentation. We first

Change detection between two images is challenging and needed in a wide variety of imaging applications. Several approaches have been yet developed, especially methods based

The two prediction modes are evaluated with only the geometric compensation enabled (“geo”) and both the geometric and photometric compensations enabled (“geo+photo”). The

case the bag-of-features image search system becomes very similar to an ap- proach which matches individual descriptors, i.e., for very large vocabularies the number of visual words

Denoising or restoration methods must then preserve space-time discontinuities while minimizing the error between the unknown original noise-free image sequence and the