Implementation of Wiener Algorithm for Spectral Reflectance Reconstruction of 3 and 6 Channel Images

Wiener estimation is a widely used technique for the spectral reflectance reconstruction of colored objects. In our study the reflectance estimation of 3-channel images acquired using traditional RGB camera was compared with that of 6-channel images captured by a modified 6-channel camera. 240 patches of ColorChecker DC Chart were used for training and testing of the models.Their performance was assessed via quality metrics PSNR, RMSE and CIE DE2000 based on the reconstructed and spectrophotometrically measured reflectance values. Compared to the 3-channel models, 6-channel models in general provided better results. Lowest color difference CIE DE2000 was obtained when using 10 calculation terms in the 3-channel algorithm and 13 terms in the 6-channel. Best reconstruction models, i.e. lowest CIE DE2000 and RMSE and highest PSNR values, were found for the skin and neutral tones while the performance was the poorest with the saturated color patches. The obtained results can be of use in various practical applications, such as in a printing workflow with high precision color rendering or for accurate digitization of paintings and other works of art

Representing Outliers for Improved Multi-Spectral Data Reduction

Large multi-spectral datasets such as those created by multi-spectral images require a lot of data storage. Compression of these data is therefore an important problem. A common approach is to use principal components analysis (PCA) as a way of reducing the data requirements as part of a lossy compression strategy. In this paper, we employ the fast MCD (Minimum Covariance Determinant) algorithm, as a highly robust estimator of multivariate mean and covariance, to detect outlier spectra in a multi-spectral image. We then show that by removing the outliers from the main dataset, the performance of PCA in spectral compression significantly increases. However, since outlier spectra are a part of the image, they cannot simply be ignored. Our strategy is to cluster the outliers into a small number of groups and then compress each group separately using its own cluster-specific PCAderived bases. Overall, we show that significantly better compression can be achieved with this approach

Multispectral acquisition of large-sized pictorial surfaces

Multispectral acquisition of artworks has recently received considerable attention in the image processing community. Quite understandably, so far this attention has mainly focused on paintings, given their predominant role in museum collections. It is worth pointing out that the instrumentation and procedures used for acquiring regular paintings are not suited for the multispectral acquisition of large-sized painted surfaces such as frescoed halls and great paintings. Given the relevance of such artifacts, and their widespread presence in churches or historical buildings due to their social function, the problem of finding suitable techniques for their acquisition is certainly worth addressing. This paper focuses on multispectral acquisition of large-sized pictorial surfaces, systematically addressing the practical issues related to the acquisition equipment and procedure. Given the crucial role played by the illumination in this application, special attention is given to this issue. The proposed approach is supported by experimental results

Procjena kolorimetrijskih vrijednosti pigmenata slike korištenjem hiperspektralnih informacija

Procjena kolorimetrijskih vrijednosti pigmenata umjetničke slike korištenjem spektralnih informacija proširena je na hiperspektralne informacije. Razlog tome je dostupnost specijalno napravljenih hiperspektralnih kamera. Hiperspektralnom informacijom dobivamo značajno više podataka o mjerenom objektu, u ovom slučaju je to određeni pigment i vezivo korišteno u stvaranju slike. Fizikalne metode korištene u klasičnoj restauraciji slika daju nam uvid u kemijski sastav pigmenata na temelju kojeg se dalje zaključuju i točno određuju pigmenti slike. Svaki pigment i vezivo u kombinaciji daju specifičnu informaciju. Tako definiran spektar na tek korištenom pigmentu te usporedba tog pigmenta nakon određenog vremenskog razdoblja daju nam osnovu za digitalno predviđanje i ponašanje u procesu starenja pigmenta i pripadajućeg veziva. U metodolološkom dijelu rada slijedi obrada mjerenih podataka korištenjem Matlab-a pomoću kojeg je omogućeno predviđanje podataka. Rezultati modeliranja izraženi su kolorimetrijskim vrijednostima u cilju jednostavnije primjene u digitalnom okruženju i komunikacije prostora boja. Postojanje sličnih rješenja trebalo bi olakšati konzervacijski, kasnije i restauracijski, rad gdje je informacija o ponašanju određenih slikarskih boja u vremenskoj dimenziji vrlo značajna. U cilju uštede vremena i upotrebljenih materijala, poput pigmenata i veziva, korištenje metoda zapisa koje nemaju degradacijsko djelovanje na ispitivani objekt uzimamo kao pozitivan pristup. Predviđanje kolorimetrijskih vrijednosti namjenjenih korištenju u digitalnom okruženju pomoću spektralnih i hiperspektralnih informacija trebalo bi omogućiti preciznije modeliranje željenog produkta odnosno vrijednosti boje

La restauración del Retrato Trivulzio de Antonello da Messina

El artículo presenta la intervención llevada a cabo en 2006 sobre el Retrato de hombre de Antonello da Messina, que pertenece a las colecciones del Museo Cívico de Arte Antiguo del Palacio Madame. The article presents the intervention carried out in 2006 about the Portrait of a man of Antonello da Messina, which belongs to the collections of the Civic Museum of Ancient Art of the Madame Palace.El artículo presenta la intervención llevada a cabo en 2006 sobre el Retrato de hombre de Antonello da Messina, que pertenece a las colecciones del Museo Cívico de Arte Antiguo del Palacio Madame.&nbsp