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High Frequency Components Preserved Canvas Artifacts Removal

Neethu Unnikrishnan, R. G. Ragi

Abstract


ABSTRACT

This paper mainly discuss about the removal of canvas artifacts from high-resolution digital photographs and X-ray images of paintings on canvas. Both imaging modalities are common investigative tools in art antiquity and art preservation. Canvas artifacts manifest themselves very differently according to the acquisition modality; they can hinder the visual reading of the painting by art experts, for example, in preparing a restoration campaign. Computer-aided canvas removal is desired for restorers when the painting on canvas they are get ready to restore has attained over the years a much more noticeable texture.  Propose a new algorithm that combines a cartoon-texture decay method with adaptive multiscale thresholding in the frequency domain to separate and suppress the canvas components. The proposed algorithm outperforms preceding methods proposed for visual photographs such as morphological component analysis and Wiener filtering and it also works for the digital removal of canvas artifacts in X-ray images. DeCanv is a source separation method for the removal of periodic structures, and applied it in the context of the novel application of canvas removal from digital image acquisitions of paintings on canvas.

 

Keywords: Digital painting analysis, canvas removal, denoising, periodic noise, source separation.


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References


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