Silvia Cariolo

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The large diffusion on consumer market of digital image devices suggests solutions for automatic image classification with the aim to automatically drive camera settings (i.e. exposure, focus, shutter speed, etc.), that are usually fixed as presets, or develop chromatic corrections based on the expected color rendition [5]. Although it is difficult to fully(More)
The paper proposes a new method devoted to identify specific semantic regions on CFA (Color Filtering Array) data images representing natural scenes. Making use of collected statistics over a large dataset of high quality natural images, the method uses spatial features and the Principal Component Analysis (PCA) in the HSL and normalized-RG color spaces.(More)
In the method, the membership image is produced through a multi-stage process that contemplates a ?rst punctual classi?cation stage generating a rough membership image, followed by a loW-pass ?ltering of regionaliZation of the image through a down-sampling of the image followed by an up-sampling of the image, and in a further step of merging the regions(More)
An automatic natural scene images classifier and enhancer is presented. It works mainly by combined chromatic and positional criterions in order to classify and enhance portraits and landscapes natural scenes images. Various image processing applications can easily take advantage from the proposed solution, e.g. automatic drive camera settings for the(More)
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