Multispectral Image Matting of Ancient Chinese Paintings

Simple item page
dc.contributor.authorZhang, Jiawanen_US
dc.contributor.authorZhang, Yien_US
dc.contributor.authorZhang, Shengpingen_US
dc.contributor.authorYan, Lixiaen_US
dc.contributor.authorChen, Jinyanen_US
dc.contributor.editorA. Day and R. Mantiuk and E. Reinhard and R. Scopignoen_US
dc.date.accessioned2014-02-06T15:10:40Z
dc.date.available2014-02-06T15:10:40Z
dc.date.issued2011en_US
dc.description.abstractDigital matting, the process of extracting a foreground object from an image, is an important task in image and video editing. Applying matting techniques to Chinese painting image processing can create novel composites or facilitate other editing tasks. However, Chinese paintings are painted on xuan-paper or silk, the semi-transparent strokes resulted from the diffusion and penetration of ink and pigments make it difficult to extract the foreground from the paintings only based on three-band image. In this paper, we demonstrate a new multispectral image matting technique for Chinese painting image editing. We derive a similarity function from Kubelka-Munk turbid media theory, and this allows us to find the optimal alpha matte. By adopting multispectral matting method, semitransparent foreground stroke can be extracted from the overlay of background strokes. Experimental results show the approach acceptable and promising.en_US
dc.description.seriesinformationEurographics 2011 - Areas Papersen_US
dc.identifier.issn1017-4656en_US
dc.identifier.urihttps://doi.org/10.2312/EG2011/areas/009-015en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation-Display algorithms; I.3.4 [Computer Graphics]: Graphics Utilities-Graphics editorsen_US
dc.titleMultispectral Image Matting of Ancient Chinese Paintingsen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
009-015.pdf
Size:
715.85 KB
Format:
Adobe Portable Document Format
Download
Collections
Areas Papers