Search results for "signal processing"

Biologically Inspired Model for Inference of 3D Shape from Texture.

2015

A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can…

Deep Gaussian Processes for Geophysical Parameter Retrieval

2018

This paper introduces deep Gaussian processes (DGPs) for geophysical parameter retrieval. Unlike the standard full GP model, the DGP accounts for complicated (modular, hierarchical) processes, provides an efficient solution that scales well to large datasets, and improves prediction accuracy over standard full and sparse GP models. We give empirical evidence of performance for estimation of surface dew point temperature from infrared sounding data.

Boolean operations with implicit and parametric representation of primitives using R-functions

2005

We present a new and efficient algorithm to accurately polygonize an implicit surface generated by multiple Boolean operations with globally deformed primitives. Our algorithm is special in the sense that it can be applied to objects with both an implicit and a parametric representation, such as superquadrics, supershapes, and Dupin cyclides. The input is a constructive solid geometry tree (CSG tree) that contains the Boolean operations, the parameters of the primitives, and the global deformations. At each node of the CSG tree, the implicit formulations of the subtrees are used to quickly determine the parts to be transmitted to the parent node, while the primitives' parametric definition …

Entire reflective object surface structure understanding based on reflection motion estimation

2015

An sub-segmentation method for the reflective surface structure understanding.The use of reflection motion features as spatiotemporal coherence for video segmentation.Straightforward implementation.A building block for object recognition. The presence of reflection on a surface has been a long-standing problem for object recognition since it brings negative effects on object's color, texture and structural information. Because of that, it is not a trivial task to recognize the surface structure affected by the reflection, especially when the object is entirely reflective. Most of the cases, reflection is considered as noise. In this paper, we propose a novel method for entire reflective obj…

A Successive Umbrella Sampling Algorithm to Sample and Overcome Free Energy Barriers

2006

An Italian input–output model for the assessment of energy and environmental benefits arising from retrofit actions of buildings

2013

Abstract The paper presents an energy and environmental extended input–output model combined with the life cycle assessment, applied to assess the energy and environmental benefits arising from the Italian policy of tax deduction for energy retrofit actions of buildings. The study allowed to assess the advantages due to the above policy, taking into account both direct and indirect energy saving and avoided CO 2 emissions obtained with the retrofit actions and indirect energy consumption and related CO 2 emissions due to the realization of the above actions. Moreover, the authors defined an original model to assess the indirect rebound effect caused by the energy saving actions. The obtaine…

The S-kernel: A measure of symmetry of objects

2007

In this paper we introduce a new symmetry feature named ''symmetry kernel'' (SK) to support a measure of symmetry. Given any symmetry transform S, SK of a pattern P is the maximal included symmetric sub-set of P for all directions and shifts. We provide a first algorithm to exhibit this kernel where the centre of symmetry is assumed to be the centre of mass. Then we prove that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its symmetric version. That leads to a second algorithm. The associated symmetry measure is a modified difference between the respective surfaces of a pattern and its kernel. A series of experiments supports the actual algorit…

Superresolved digital in-line holographic microscopy for high-resolution lensless biological imaging.

2010

Digital in-line holographic microscopy (DIHM) is a modern approach capable of achieving micron-range lateral and depth resolutions in three-dimensional imaging. DIHM in combination with numerical imaging reconstruction uses an extremely simplified setup while retaining the advantages provided by holography with enhanced capabilities derived from algorithmic digital processing. We introduce superresolved DIHM incoming from time and angular multiplexing of the sample spatial frequency information and yielding in the generation of a synthetic aperture (SA). The SA expands the cutoff frequency of the imaging system, allowing submicron resolutions in both transversal and axial directions. The pr…

Urban monitoring using multi-temporal SAR and multi-spectral data

2006

In some key operational domains, the joint use of synthetic aperture radar (SAR) and multi-spectral sensors has shown to be a powerful tool for Earth observation. In this paper, we analyze the potentialities of combining interferometric SAR and multi-spectral data for urban area characterization and monitoring. This study is carried out following a standard multi-source processing chain. First, a pre-processing stage is performed taking into account the underlying physics, geometry, and statistical models for the data from each sensor. Second, two different methodologies, one for supervised and another for unsupervised approaches, are followed to obtain features that optimize the urban rela…

Surpassing digital holography limits by lensless object scanning holography.

2012

We present lensless object scanning holography (LOSH) as a fully lensless method, capable of improving image quality in reflective digital Fourier holography, by means of an extremely simplified experimental setup. LOSH is based on the recording and digital post-processing of a set of digital lensless holograms and results in a synthetic image with improved resolution, field of view (FOV), signal-to-noise ratio (SNR), and depth of field (DOF). The superresolution (SR) effect arises from the generation of a synthetic aperture (SA) based on the linear movement of the inspected object. The same scanning principle enlarges the object FOV. SNR enhancement is achieved by speckle suppression and c…