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Examples of Our Work Interactive visual information processing, interactive
image retrieval, segmentation .... (link ...) Example-based
Image Processing ... (link ...) Unifying
histogram-based image content descriptor for
content-based image retrieval - the CPAM and AI framework
... (link ...) Integrated
framework for image coding, indexing, and
content-based image retrieval ... (link ...) Visual guided
browsing and navigation for fast image
retrieval ... (link ...) Fast comprehensive
tone mapping for high dynamic range
image visualization ... (link ...) Colorizing black
and white photos ... Making beautiful pictures, computational
photography ... (link ....) Machine learning, pattern recognition ... (link ...) Image data mining, image and feature co-clustering .... (link...) |
 A monochrome image is
scribbled with some initial colors (left), these colors are then
propagated to the whole image using our color by linear neighborhood
embedding method (middle). For reference, the original image is shown
on the right.
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Colorizing black and white photos We have deveoped a
computational method for colorizing black and white photos. Following
computational methods of the locally linear embedding (LLE) algorithm,
we compute the geometry of the monochrome image by solving a
constrained least squares problem and embed the computed geometry in
the chrominance images by solving a linearly constrained quadratic
optimization problem, both in closed forms. The two steps of our
computational algorithm are Step 1: Compute the
neighbourhood relationships from the achromatics image
 More examples can be found in this page |
