Graph-based methods for simultaneous smoothing and sharpening of color images

[EN] In this work we introduce an image characterization of pixels based on local graphs that allows to distinguish different local regions around a pixel. This separation also permits us to develop a method for determining the role of each pixel in a neighborhood of any other, either for smoothing or for sharpening. Two methods for simultaneously conducting both processes are provided. Our solution overcomes the drawbacks of the classic two steps sequential smoothing and sharpening process: enhancing details while reducing noise and not losing critical information. The parameters of the methods are adjusted in two different ways: through observers visual quality optimization and with an objective optimization criterion. The results show that our methods outperform other recent state-of-the-art ones.We thank F. Russo for providing the implementation of the Fuzzy method and V. Ratmer, and Y.Y. Zeevi for providing the implementation of the FAB method. Cristina Jordan acknowledges the support of grant TEC2016-79884-C2-2-R. Samuel Morillas acknowledges the support of grant MTM2015-64373-P (MINECO/FEDER, Spain, UE).Pérez-Benito, C.; Jordan-Lluch, C.; Conejero, JA.; Morillas, S. (2019). Graph-based methods for simultaneous smoothing and sharpening of color images. Journal of Computational and Applied Mathematics. 350:380-395. https://doi.org/10.1016/j.cam.2018.10.031S38039535

Artistic minimal rendering with lines and blocks

Many non-photorealistic rendering techniques exist to produce artistic effects from given images. Inspired by various artists, interesting effects can be produced by using a minimal rendering, where the minimum refers to the number of tones as well as the number and complexity of the primitives used for rendering. Our method is based on various computer vision techniques, and uses a combination of refined lines and blocks (potentially simplified), as well as a small number of tones, to produce abstracted artistic rendering with sufficient elements from the original image. We also considered a variety of methods to produce different artistic styles, such as colour and 2-tone drawings, and use semantic information to improve renderings for faces. By changing some intuitive parameters a wide range of visually pleasing results can be produced. Our method is fully automatic. We demonstrate the effectiveness of our method with extensive experiments and a user study

ARHON: A Multimedia Database Design for Image Documents

In this paper we present the design and initial implementation of a multimedia system for historical documents. The system, currently under development at FORTH, will be used by the Vikelea Municipal Library of archives at Heraklion, Crete. The material consists of historical documents that need to be digitized, indexed and continuously annotated by scholars so that the value of the archive will increase by its use. We present the design architecture and initial implementation of a clientserver model for the creation, maintenance and use of such a digital archive. Also, we present a technique for marking-up different media to provide rapid entering of semantic information The user can interactively markup parts of the representation on the medium of choice (e.g. areas on a document image) and associate local information with text, images, sound-clips, video or subparts of them without altering the original. The output is XML files that can be parsed by viewers to navigate through the s..

Enhancing underexposed images preserving the original mood

In the present article we focus on enhancing the contrast of images with low illumination that present large underexposed regions. Most of these images represent night images. When applying standard contrast enhancement techniques, usually the night mood is modified, and also a noise over-enhancement within the darker regions is introduced. In a previous work we have described our local contrast correction algorithm designed to enhance images where both underexposed and overexposed regions are simoultaneously present. Here we show how this algorithm is able to automatically enhance night images, preserving the original mood. To further improve the performance of our method we also propose here a denoising procedure where the strength of the smoothing is a function of an estimated level of noise and it is further weighted by a saliency map. The method has been applied to a proper database of outdoor and indoor underexposed images. Our results have been qualitatively compared with well know contrast correction methods. \ua9 2011 Springer-Verlag Berlin Heidelberg