Search results for "image processing"
showing 10 items of 3285 documents
Kernels for Remote Sensing Image Classification
2015
Classification of images acquired by airborne and satellite sensors is a very challenging problem. These remotely sensed images usually acquire information from the scene at different wavelengths or spectral channels. The main problems involved are related to the high dimensionality of the data to be classified and the very few existing labeled samples, the diverse noise sources involved in the acquisition process, the intrinsic nonlinearity and non-Gaussianity of the data distribution in feature spaces, and the high computational cost involved to process big data cubes in near real time. The framework of statistical learning in general, and of kernel methods in particular, has gained popul…
Detection of power line insulators on digital images with the use of laser spots
2019
The massive growth of technologies used to register and process digital images allow for their application in evaluating the technical condition of power lines. However, it is not possible without a set of dedicated methods for obtaining diagnostic information based on registered video data. The method described here details the detection of power line insulators in digital images featuring diversified backgrounds using laser spots. The algorithm of detecting an insulator in analysed images is based on testing the digital signal of pixel intensity profiles read between subsequent pairs of laser points in the image. The method is comprised of the following stages: import the image with laser…
Cloud-screening algorithm for ENVISAT/MERIS multispectral images
2007
This paper presents a methodology for cloud screening of multispectral images acquired with the Medium Resolution Imaging Spectrometer (MERIS) instrument on-board the Environmental Satellite (ENVISAT). The method yields both a discrete cloud mask and a cloud-abundance product from MERIS level-lb data on a per-pixel basis. The cloud-screening method relies on the extraction of meaningful physical features (e.g., brightness and whiteness), which are combined with atmospheric-absorption features at specific MERIS-band locations (oxygen and watervapor absorptions) to increase the cloud-detection accuracy. All these features are inputs to an unsupervised classification algorithm; the cloud-proba…
A completely automated CAD system for mass detection in a large mammographic database
2006
Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…
PCA Gaussianization for image processing
2009
The estimation of high-dimensional probability density functions (PDFs) is not an easy task for many image processing applications. The linear models assumed by widely used transforms are often quite restrictive to describe the PDF of natural images. In fact, additional non-linear processing is needed to overcome the limitations of the model. On the contrary, the class of techniques collectively known as projection pursuit, which solve the high-dimensional problem by sequential univariate solutions, may be applied to very general PDFs (e.g. iterative Gaussianization procedures). However, the associated computational cost has prevented their extensive use in image processing. In this work, w…
Anthropogenic carbon stocks analysis in sparsely urbanized areas using remote sensing: a case study
2013
Anthropogenic carbon stocks in urbanized areas is a topic of growing importance at both local and regional scale nowadays, but its assessment is subjects to difficulties due to lack of data and spatial heterogeneity of the target. Remote sensing of urban areas has demonstrated its usefulness in assessing phenomena such as soil sealing and surface imperviousness, which are considered to be effective indicators of urbanization. This work presents a preliminary study of mid resolution satellite data capabilities in providing information about anthropogenic carbon stocks over the area of Emilia-Romagna region in Northern Italy. This has been done through a dual approach consisting of: (1) a dir…
A novel strategy for solving the stochastic point location problem using a hierarchical searching scheme
2014
Stochastic point location (SPL) deals with the problem of a learning mechanism (LM) determining the optimal point on the line when the only input it receives are stochastic signals about the direction in which it should move. One can differentiate the SPL from the traditional class of optimization problems by the fact that the former considers the case where the directional information, for example, as inferred from an Oracle (which possibly computes the derivatives), suffices to achieve the optimization-without actually explicitly computing any derivatives. The SPL can be described in terms of a LM (algorithm) attempting to locate a point on a line. The LM interacts with a random environme…
Automatic Processing Scheme for Low Laser Invasiveness Electro Optical Frequency Mapping mode
2016
International audience; Electro optical techniques are efficient backside contactless techniques usually used for design debug and defect location in modern VLSI. Unfortunately, the signal to noise ratio is quite low and depends on laser power with potential device stress due to long acquisition time or high laser power, especially in up to date technologies. Under these conditions, to maintain a good signal or image quality, specific signal or image processing techniques can be implemented. In this paper, we proposed a new spatial filtering by stationary wavelets and contrast enhancement which allows the use of low laser power and short acquisition time in image mode.
On the Extension of the DIRECT Algorithm to Multiple Objectives
2020
AbstractDeterministic global optimization algorithms like Piyavskii–Shubert, direct, ego and many more, have a recognized standing, for problems with many local optima. Although many single objective optimization algorithms have been extended to multiple objectives, completely deterministic algorithms for nonlinear problems with guarantees of convergence to global Pareto optimality are still missing. For instance, deterministic algorithms usually make use of some form of scalarization, which may lead to incomplete representations of the Pareto optimal set. Thus, all global Pareto optima may not be obtained, especially in nonconvex cases. On the other hand, algorithms attempting to produce r…
On utilizing an enhanced object partitioning scheme to optimize self-organizing lists-on-lists
2020
With the advent of “Big Data” as a field, in and of itself, there are at least three fundamentally new questions that have emerged, namely the Artificially Intelligence (AI)-based algorithms required, the hardware to process the data, and the methods to store and access the data efficiently. This paper (The work of the second author was partially supported by NSERC, the Natural Sciences and Engineering Council of Canada. We are very grateful for the feedback from the anonymous Referees of the original submission. Their input significantly improved the quality of this final version.) presents some novel schemes for the last of the three areas. There have been thousands of papers written rega…