Search results for "Real image"
showing 10 items of 39 documents
Optical calibration of a multispectral imaging system based on interference filters
2005
We present a new approach to optically calibrate a multispectral imaging system based on interference filters. Such a system typically suffers from some blurring of its channel images. Because the effectiveness of spectrum reconstruction depends heavily on the quality of the acquired channel images, and because this blurring negatively affects them, a method for deblurring and denoising them is required. The blur is modeled as a uniform intensity distribution within a circular disk. It allows us to characterize, quantitatively, the degradation for each channel image. In terms of global reduction of the blur, it consists of the choice of the best channel for the focus adjustment according to…
Quasi-Newton approach to nonnegative image restorations
2000
Abstract Image restoration, or deblurring, is the process of attempting to correct for degradation in a recorded image. Typically the blurring system is assumed to be linear and spatially invariant, and fast Fourier transform (FFT) based schemes result in efficient computational image restoration methods. However, real images have properties that cannot always be handled by linear methods. In particular, an image consists of positive light intensities, and thus a nonnegativity constraint should be enforced. This constraint and other ways of incorporating a priori information have been suggested in various applications, and can lead to substantial improvements in the reconstructions. Neverth…
Generative Adversarial Networks in Cardiology
2021
A B S T R A C T Generative Adversarial Networks (GANs) are state-of-the-art neural network models used to synthesize images and other data. GANs brought a considerable improvement to the quality of synthetic data, quickly becoming the standard for data generation tasks. In this work, we summarize the applications of GANs in the field of cardiology, including generation of realistic cardiac images, electrocardiography signals, and synthetic electronic health records. The utility of GAN-generated data is discussed with respect to research, clinical care, and academia. Moreover, we present illustrative examples of our GAN-generated cardiac magnetic resonance and echocardiography images, showin…
Tensor product multiresolution analysis with error control for compact image representation
2002
A class of multiresolution representations based on nonlinear prediction is studied in the multivariate context based on tensor product strategies. In contrast to standard linear wavelet transforms, these representations cannot be thought of as a change of basis, and the error induced by thresholding or quantizing the coefficients requires a different analysis. We propose specific error control algorithms which ensure a prescribed accuracy in various norms when performing such operations on the coefficients. These algorithms are compared with standard thresholding, for synthetic and real images.
A genetic algorithm for image segmentation
2002
The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm.
Dissecting and Reassembling Color Correction Algorithms for Image Stitching
2018
This paper introduces a new compositional framework for classifying color correction methods according to their two main computational units. The framework was used to dissect fifteen among the best color correction algorithms and the computational units so derived, with the addition of four new units specifically designed for this work, were then reassembled in a combinatorial way to originate about one hundred distinct color correction methods, most of which never considered before. The above color correction methods were tested on three different existing datasets, including both real and artificial color transformations, plus a novel dataset of real image pairs categorized according to …
Il Dioniso delle "Baccanti" e i "piegatori di pini". Polivalenza di un'immagine leggendaria
2021
This paper investigates the mythical and ritual background of Dionysus’ representation as “fir-bender” in Euripides’ "Bacchae" (ll. 1061 ff.), in an attempt to shed light not only on the dramaturgical aspects of the tragic plot, but also on the cultural categories that make this representation intelligible to the Athenian audience at the end of the fifth century BC. Following Louis Gernet’s historical-anthropological approach based on the notion of "polyvalence des images", this paper aims to define a mythical pattern – the connection between the bending of a tree and the dismemberment of a human victim – already attested in the Attic legend of Theseus and Sinis, in which both characters se…
Short baseline line matching for central imaging systems
2012
We develop a generic line matching method especially applicable to omnidirectional images taken from constructed scenes with short baseline motion where the motion of the imaging system between two views is mainly an arbitrary rotation and the translation of the camera between two views with respect to its distance to the imaged scene is negligible. We start by studying the relationship between images of lines on unitary sphere followed by proposing a simple algorithm for simultaneously matching vanishing points and lines. The developed algorithm is very simple, yet it works on images captured by all types of central imaging systems, including perspective, fish-eye and catadioptric images. …
Which Is Which? Evaluation of Local Descriptors for Image Matching in Real-World Scenarios
2019
Matching with local image descriptors is a fundamental task in many computer vision applications. This paper describes the WISW contest held within the framework of the CAIP 2019 conference, aimed at benchmarking recent descriptors in challenging planar and non-planar real image matching scenarios. According to the contest results, the descriptors submitted to the competition, most of which based on deep learning, perform significantly better than the current state-of-the-art in image matching. Nonetheless, there is still room for improvement, especially in the case of non-planar scenes.
A Generic Method of Line Matching for Central Imaging Systems under Short-Baseline Motion
2009
Line matching across images taken by a central imaging system (perspective or catadioptric) with focus on short baseline motion of the system is proposed. The relationship between images of lines on unitary sphere is studied and a simple algorithm for matching lines are proposed assuming the rotation of the system is known apriori or it can be estimated from some correspondences in two views. Two methods are discussed for retrieving R in the case it is not known apriori. Experimental results on both synthetic and real images are also presented.