New PDF release: Computational Color Imaging: Third International Workshop,

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By Erik Reinhard, Tania Pouli (auth.), Raimondo Schettini, Shoji Tominaga, Alain Trémeau (eds.)

ISBN-10: 3642204031

ISBN-13: 9783642204036

This e-book constitutes the refereed court cases of the 3rd Computational colour Imaging Workshop, CCIW 2010, held in Milan, Italy, in April 2010. The sixteen revised complete papers, offered including 3 invited papers, have been rigorously reviewed and chosen from a number of submissions. The papers are prepared in topical sections on computational images, colour and notion, colour imaging, and computational imaging.

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Read Online or Download Computational Color Imaging: Third International Workshop, CCIW 2011, Milan, Italy, April 20-21, 2011. Proceedings PDF

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Additional info for Computational Color Imaging: Third International Workshop, CCIW 2011, Milan, Italy, April 20-21, 2011. Proceedings

Sample text

From a purely physical perspective, the absorptions of the K colorant across the spectrum and the unwanted absorptions indicate that the individual R, G, and B channels cannot directly isolate a single separation. However, as we illustrate in the sequel, and as described in greater detail in [17], the combination of physical insight with mathematical analysis does indeed lead to an effective solution whereby the four color separations can be estimated, which in turn enable per separation phase modulation halftone watermark embedding.

The exposition in the present paper borrows heavily from these prior publications. Our previous paper on the broader theme [23] included as examples, work on show-through correction [20] and set-theoretic estimation for subtractive color [18, 19]. We encourage readers whose interests may have been stimulated by specific examples, to follow the relevant publications for additional information and details. Clearly, we cannot and do not claim to monopolize the broader underlying theme of this paper; a far larger set of equally good and perhaps better examples can be found in the works of other researchers.

To evaluate quantitatively the performance the method it is compared to four state of art segmentation algorithms using the Berkeley image database (Table 3). Figure 8 shows qualitative results of the method applying different parameters to obtain from fine to coarse segmentation. In all cases the segments behave consistently. (a) (b) (c) Fig. 7. Example of MR extraction (a) Original image. (b) Result of the creassenes operator on a RG/BY chromaticity space. Extracted ridge points are given in black on top of the distribution.

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Computational Color Imaging: Third International Workshop, CCIW 2011, Milan, Italy, April 20-21, 2011. Proceedings by Erik Reinhard, Tania Pouli (auth.), Raimondo Schettini, Shoji Tominaga, Alain Trémeau (eds.)


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