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Reflectance recovery using localised weighted method

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Titel Reflectance recovery using localised weighted method
Serientitel The Sixth European Conference on Colour in Graphics, Imaging, and Vision (CGIV 2012)
Teil 30
Anzahl der Teile 31
Autor Chou, Yi-Fan
Cheung, Vien
Li, Changjun
Luo, M. Ronnier
Lee, San-Liang
Lizenz CC-Namensnennung - keine Bearbeitung 2.0 UK: England & Wales:
Sie dürfen das Werk in unveränderter Form zu jedem legalen Zweck nutzen, vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen.
DOI 10.5446/31462
Herausgeber River Valley TV
Erscheinungsjahr 2012
Sprache Englisch

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Fachgebiet Informatik
Abstract This paper evaluated four conventional methods for reflectance recovery: smoothness method [1], principle component analysis [2], basis functions with smoothness constraint [3] and Wiener estimation [4,5]. Most of these methods adopt a “learning-based” procedure with a training set. Modifications based on the training set were applied for improving the reflectance recovery performance. This paper described combined methods involving the application of localised training data and localised training data with a weighted matrix to the four recovery methods [1-5]. All these methods were applied to recover reflectance from XYZ values for two datasets. Both the training and testing performance were evaluated in terms of CIEDE2000 colour differences. The results showed that the performance of the methods with localised training data significantly improved. There are also limited improvements by applying the weighted matrix. Overall, the localised weighted method (using a local training set with a weighted matrix) with Weiner estimation method performed the best.

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