Papers by Giuseppe Papari
Proceedings of SPIE, Feb 15, 2007
Publication in the conference proceedings of EUSIPCO, Florence, Italy, 2006
In this thesis it is explored how far a computer can perform the task of preserving the content o... more In this thesis it is explored how far a computer can perform the task of preserving the content of an image while removing totally or partially its texture information. This problem is studied in two application fields: contour detection and artistic imaging. Concerning contour detection, the state of the art is first reviewed. Several classes of local algorithms are considered, which are mainly based on differential analysis, statistical approaches, phase congruency, rank order filters, and combinations thereof. More sophisticated global methods based on the computation of contour saliency, perceptual grouping, relaxation labeling and active contours are considered too. Then, algorithms for contour detector are developed, which are inspired by several aspects of both low and high level of the human visual system. In particular, a biologically motivated multiresolution contour detector with Bayesian denoising and surround inhibition is proposed, which takes into account several low ...
SPIE Proceedings, 2006
In this paper we propose a multiscale biologically motivated technique for contour detection by t... more In this paper we propose a multiscale biologically motivated technique for contour detection by texture suppression. Standard edge detectors reacts to all the local luminance changes, irrespective whether they are due to the contours of the objects represented in the scene, rather than to natural texture like grass, foliage, water, etc. Moreover, edges due to texture are often stronger than edges due to true contours. This implies that further processing is needed to discriminate true contours from texture edges. In this contribution we exploit the fact that, in a multiresolution analysis, at coarser scales, only the edges due to object contours are present while texture edges disappear. This is used in combination with surround inhibition, a biologically motivated technique for texture suppression, in order to build a contour detector which is insensitive to texture. The experimental results show that our approach is also robust to additive noise.
Image Processing: Algorithms and Systems V, 2007
ABSTRACT What visually distinguishes a painting from a photograph is often the absence of texture... more ABSTRACT What visually distinguishes a painting from a photograph is often the absence of texture and the sharp edges: in many paintings, edges are sharper than in photographic images while textured areas contain less detail. Such artistic effects can be achieved by filters that smooth textured areas while preserving, or enhancing, edges and corners. However, not all edge preserving smoothers are suitable for artistic imaging. This study presents a generalization of the well know Kuwahara filter that is aimed at obtaining an artistic effect,. Theoretical limitations of the Kuwahara filter are discussed and solved by the new nonlinear operator proposed here. Experimental results shows that the proposed operator produces painting-like output images and is robust to corruption of the input image such as blurring. Comparison with existing techniques shows situations where traditional edge preserving smoothers that are commonly used for artistic imaging fail while our approach produces good results.
2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009
Stereo imaging is an important area of image and video processing, with exploding progress in the... more Stereo imaging is an important area of image and video processing, with exploding progress in the last decades. An open issue in this field is the understanding of the conditions under which the straightforward application of a given image processing operator to both the left and right image of a stereo pair preserves the stereoscopic perception. In this paper, we explore this problem with application to artistic imaging and we prove that, unlike other methods, artistic operators based on edge preserving smoothing have this desirable property. We also present a novel multiresolution artistic operator, purposely designed for stereo images, which enhances the perception of three-dimensionality by means of a depth driven local scale control.
Lecture Notes in Computer Science, 2005
We propose an algorithm that groups points similarly to how human observers do. It is simple, tot... more We propose an algorithm that groups points similarly to how human observers do. It is simple, totally unsupervised and able to find clusters of complex and not necessarily convex shape. Groups are identified as the connected components of a Reduced Delaunay Graph (RDG) that we define in this paper. Our method can be seen as an algorithmic equivalent of the gestalt law of perceptual grouping according to proximity. We introduce a measure of dissimilarity between two different groupings of a point set and use this measure to compare our algorithm with human visual perception and the k-means clustering algorithm. Our algorithm mimics human perceptual grouping and outperforms the k-means algorithm in all cases that we studied. We also sketch a potential application in the segmentation of structural textures.
Lecture Notes in Computer Science, 2009
The theory of Glass patterns naturally combines three essential aspects of painterly artworks: pe... more The theory of Glass patterns naturally combines three essential aspects of painterly artworks: perception, randomness, and geometric structure. Therefore, it seems a suitable framework for the development of mathematical models of the visual properties that distinguish paintings from photographic images. With this contribution, we introduce a simple mathematical operator which transfers the microstructure of a Glass pattern to an input image, and we show that its output is perceptually similar to a painting. An efficient implementation is presented. Unlike most of the existing techniques for unsupervised painterly rendering, the proposed approach does not introduce 'magic numbers' and has a nice and compact mathematical description, which makes it suitable for further theoretical analysis. Experimental results on a broad range of input images validate the effectiveness of the proposed method in terms of lack of undesired artifacts, which are present with other existing methods, and easy interpretability of the input parameters.
Lecture Notes in Computer Science, 2009
The interpolation problem of irregularly distributed data in a multidimensional domain is conside... more The interpolation problem of irregularly distributed data in a multidimensional domain is considered. A modification of the inverse distance weighting interpolation formula is proposed, making computation time independent of the number of data points. Only the first K neighbors of a given point are considered, instead of the entire dataset. Additional factors are introduced, preventing discontinuities on points where the
2006 International Conference on Image Processing, 2006
In natural images, luminance changes occur both on object contours and on textures. Often, the la... more In natural images, luminance changes occur both on object contours and on textures. Often, the latter are stronger than the former, thus standard edge detectors fail in isolating object contours from texture. To overcome this problem, we propose a multiresolution contour detector motivated by biological principles. At each scale, texture is suppressed by using a bipolar surround inhibition process. The binary contour map is obtained by a contour selection criterion that is more effective than the classical hysteresis thresholding. Robustness to noise is achieved by Bayesian gradient estimation.
2010 20th International Conference on Pattern Recognition, 2010
In this paper, we perform approximate steering of the elongated 2D Hermite-Gauss functions with r... more In this paper, we perform approximate steering of the elongated 2D Hermite-Gauss functions with respect to rotations and provide a compact analytical expressions for the related basis functions. A special notation introduced here considerably simplifies the derivation and unifies the cases of even and odd indices. The proposed filters are applied to edge detection. Quantitative analysis shows a performance increase of about 12.5% in terms of the Pratt's figure of merit with respect to the well-established Gaussian gradient proposed by Canny.
2010 IEEE International Conference on Image Processing, 2010
We provide a closed form, both in the spatial and in the frequency domain, of a family of wavelet... more We provide a closed form, both in the spatial and in the frequency domain, of a family of wavelets which arise from steering elongated Hermite-Gauss filters. These wavelets have interesting mathematical properties, as they form new dyadic families of eigenfunctions of the 2D Fourier transform, and generalize the well known Laguerre-Gauss harmonics. A special notation introduced here greatly simplifies our proof and unifies the cases of even and odd orders. Applying these wavelets to edge detection increases the performance of about 12.5% with respect to standard methods, in terms of the Pratt's figure of merit, both for noisy and noise-free input images.
Estimating surface circulation from satellite images is a hot subject for a large range of applic... more Estimating surface circulation from satellite images is a hot subject for a large range of applications. Motion estimation from image data has been studied for long in the literature of Image Processing, and more recently in that of Data Assimilation (DA). This paper describes how the construction of dedicated spaces for projecting motion and image fields allows applying DA methods with a reduced model and eases the estimation of surface circulation on the whole Black Sea basin.
2013 IEEE International Conference on Computer Vision, 2013
This paper describes modeling and numerical computation of orthogonal bases, which are used to de... more This paper describes modeling and numerical computation of orthogonal bases, which are used to describe images and motion fields. Motion estimation from image data is then studied on subspaces spanned by these bases. A reduced model is obtained as the Galerkin projection on these subspaces of a physical model, based on Euler and optical flow equations. A data assimilation method is studied, which assimilates coefficients of image data in the reduced model in order to estimate motion coefficients. The approach is first quantified on synthetic data: it demonstrates the interest of model reduction as a compromise between results quality and computational cost. Results obtained on real data are then displayed so as to illustrate the method.
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Papers by Giuseppe Papari