Search results for "pattern"
showing 10 items of 4203 documents
An interpolation-based data fusion scheme for enhancing the resolution of thermal image sequences
2014
In several human activities, such as agriculture and forest management, the monitoring of radiometric surface temperature is key. In particular both high spatial resolution and high acquisition rate are desirable but, due to the hardware limitations, these two characteristics are not met by the same sensor. The fusion of remotely sensed data acquired by sensors with different spatial and temporal resolution is a profitable choice to face this issue. When the real-time requirement is relaxed, the data sequence can be processed as a whole, allowing to improve the final result. Within this framework, we propose a novel batch sharpening strategy, relying on interpolation, data fusion and Bayesi…
Small Sample Biometric Recognition Based on Palmprint and Face Fusion
2009
Contactless biometrics provide high comfort and hygiene in person recognition. Because of this, such systems are better accepted by the general public. This paper proposes an adaptive, contactless, biometric system which combines two modalities: palmprint and face. The processing chain has been designed to overcome embedded system constraints and small sample set problem: after a palmprint is extracted from a hand image, Gabor filters are applied to both the palmprint and face in order to extract parameters, which are then used for classification. Fusion possibilities are also discussed and tested using a multimodal database of 130 people designed by the authors. High recognition performanc…
Improved multi-resolution image fusion
2005
This work describes an automatic technique able to fuse different images of the same scene, acquired at different settings, in order to obtain an enhanced single representation of the scene of interest by an improved picture fusion scheme. This allows the extending of the functionalities (depth of field, dynamic range) of medium and low cost digital cameras. When multi-scale decomposition is used on multi-focused images, magnification effects of the lens focusing system cause an incorrect estimation of all pixels in the final image. In our approach new techniques able to reduce these artifacts are introduced. The algorithm has been applied both on full RGB and on color filter array (CFA) im…
Ghost Detection and Removal for High Dynamic Range Images: Recent Advances
2012
23 pages; International audience; High dynamic range (HDR) image generation and display technologies are becoming increasingly popular in various applications. A standard and commonly used approach to obtain an HDR image is the multiple exposures fusion technique which consists of combining multiple images of the same scene with varying exposure times. However, if the scene is not static during the sequence acquisition, moving objects manifest themselves as ghosting artefacts in the final HDR image. Detecting and removing ghosting artefacts is an important issue for automatically generating HDR images of dynamic scenes. The aim of this paper is to provide an up-to-date review of the recentl…
Multifacet structure of observed reconstructed integral images.
2005
Three-dimensional images generated by an integral imaging system suffer from degradations in the form of grid of multiple facets. This multifacet structure breaks the continuity of the observed image and therefore reduces its visual quality. We perform an analysis of this effect and present the guidelines in the design of lenslet imaging parameters for optimization of viewing conditions with respect to the multifacet degradation. We consider the optimization of the system in terms of field of view, observer position and pupil function, lenslet parameters, and type of reconstruction. Numerical tests are presented to verify the theoretical analysis.
Roadmap on 3D integral imaging: Sensing, processing, and display
2020
This Roadmap article on three-dimensional integral imaging provides an overview of some of the research activities in the field of integral imaging. The article discusses various aspects of the field including sensing of 3D scenes, processing of captured information, and 3D display and visualization of information. The paper consists of a series of 15 sections from the experts presenting various aspects of the field on sensing, processing, displays, augmented reality, microscopy, object recognition, and other applications. Each section represents the vision of its author to describe the progress, potential, vision, and challenging issues in this field.
Diffusion equations with negentropy applied to denoise mammographic images.
2006
Mammography is a radiographic technique used for the detection of breast lesions. The analysis of the digital image normally requires a previous application of filters as a preprocessing step to reduce the noise level of the image, while preserving important details to carry out a suitable diagnostic. In the literature, there are a large amount of denoising techniques applied to different medical images. In this work we have studied the performance of a diffusive filter with a stopping condition based on the statistical concept of negentropy, applied to denoise mammographic images. The negentropy has been succesfully prove with other denoising methods as independent component analysis by th…
Image Segmentation by Deep Community Detection Approach
2017
International audience; To address the problem of segmenting an image into homogeneous communities this paper proposes an efficient algorithm to detect deep communities in the image by maximizing at each stage a new centrality measure, called the local Fiedler vector centrality (LFVC). This measure is associated with the sensitivity of algebraic connectivity to node removals. We show that a greedy node removal strategy, based on iterative maximization of LFVC, has bounded performance loss relative to the optimal, but intractable, combinatorial batch removal strategy. A remarkable feature of this method is the ability to segments the image automatically into homogeneous regions by maximizing…
Generating Hyperspectral Skin Cancer Imagery using Generative Adversarial Neural Network
2020
In this study we develop a proof of concept of using generative adversarial neural networks in hyperspectral skin cancer imagery production. Generative adversarial neural network is a neural network, where two neural networks compete. The generator tries to produce data that is similar to the measured data, and the discriminator tries to correctly classify the data as fake or real. This is a reinforcement learning model, where both models get reinforcement based on their performance. In the training of the discriminator we use data measured from skin cancer patients. The aim for the study is to develop a generator for augmenting hyperspectral skin cancer imagery. peerReviewed
High-Frequency Experimental Characterization and Modeling of Six Pack IGBTs Power Modules
2016
In this paper, a method to characterize the high-frequency (HF) behavior of six pack insulated gate bipolar transistors (IGBTs) power module (PM) is presented. The method is based on experimental measurements at the external pins of the device and it allows one to extract internal inductive and capacitive parasitic coupling without the knowledge of structural and physical parameters of the PM. The HF model of a six pack IGBTs PM has been developed, in the frequency range of 150 kHz-30 MHz, and it has been implemented in MATLAB environment. The method has been experimentally validated by comparing the frequency behavior of the PM with the simulated response. Moreover, the HF conducted distur…