Search results for "Computer Science::Computer Vision and Pattern Recognition"
showing 10 items of 193 documents
Phase-shifting digital lensless Fourier holography for high numerical aperture in-line interferometric microscopy
2012
A new common-path and phase-shifting digital lensless Fourier architecture for high numerical aperture (NA) imaging in lensless in-line holographic microscopy based on the use of a spatial light modulator (SLM) is presented and experimentally validated.
Patch-Based Image Denoising Model for Mixed Gaussian Impulse Noise Using L1 Norm
2017
Image denoising is the classes of technique used to free the image form the noise. The noise in the image may be added during the observation process due to the improper setting of the camera lance, low-resolution camera, cheap, and low-quality sensors, etc. Noise in the image may also be added during the image restoration, image transmission through the transmission media. To obtain required information from image, image must be noise free, i.e., high-frequency details must be present in the image. There are number of applications where image denoising is needed such as remote location detection, computer vision, computer graphics, video surveillance, etc. In last two decades, numbers of m…
An application of neural networks to natural scene segmentation
2006
This paper introduces a method for low level image segmentation. Pixels of the image are classified corresponding to their chromatic features.
A fully adaptive multiresolution scheme for image processing
2007
A nonlinear multiresolution scheme within Harten's framework [A. Harten, Discrete multiresolution analysis and generalized wavelets, J. Appl. Numer. Math. 12 (1993) 153-192; A. Harten, Multiresolution representation of data II, SIAM J. Numer. Anal. 33 (3) (1996) 1205-1256] is presented. It is based on a centered piecewise polynomial interpolation fully adapted to discontinuities. Compression properties of the multiresolution scheme are studied on various numerical experiments on images.
A Parallel Approach for Statistical Texture Parameter Calculation
2014
This chapter focusses on the development of a new image processing technique for the processing of large and complex images, especially SAR images. We propose here a new and effective approach that outperforms the existing methods for the calculation of high order textural parameters. With a single processor, this approach is about \(256^{n-1}\) times faster than the co-occurrence matrix approach considered as classical, where \(n\) is the order of the textural parameter for a 256-gray scales image. In a parallel environment made of N processor, this performance can almost be multiply by the factor N. Our approach is based on a new modeling of textural parameters of a generic order \(n>1\) …
Motion analysis using the novelty filter
1991
Abstract An original approach to the motion analysis, based on the novelty filter, is proposed. The novelty filter stresses the novelties occurring in a pattern representing an image of the scene under consideration with respect to patterns representing previous images of the same scene, so that visual information about the motion of the objects is obtained. The novelty filter may be implemented by a neural network architecture, taking advantage of the capabilities of massive parallelism, adaptive learning and noise robustness. The novelty filter may learn the entire trajectory of an object, through an incremental learning of a sequence of images capturing the scene, thus emphasizing if the…
Fitting flavour symmetries: the case of two-zero neutrino mass textures
2018
We present a numeric method for the analysis of the fermion mass matrices predicted in flavour models. The method does not require any previous algebraic work, it offers a $\chi^{2}$ comparison test and an easy estimate of confidence intervals. It can also be used to study the stability of the results when the predictions are disturbed by small perturbations. We have applied the method to the case of two-zero neutrino mass textures using the latest available fits on neutrino oscillations, derived the available parameter space for each texture and compared them. Textures $A_{1}$ and $A_{2}$ seem favoured because they give a small $\chi^{2}$, allow for large regions in parameter space and giv…
RADIOMETRIC CALIBRATION OF A MULTISPECTRAL CAMERA
2006
We describe in detail a method for calibrating a multispectral imaging system based on interference filters. The calibration aims to remove systematic noises introduced by the sensor, and optic and/or filters from multispectral images. After which, we can correct the non-linearity of the sensor response. Systematic noises are measured through a rigorous protocol for acquiring offset, and thermal, and Flat-Field images. The methods for acquiring Flat-Field image, and linearizing sensor response are novel and particularly efficient in the case of a multispectral imaging system. Indeed, in such a system, the reconstruction of a spectrum for each pixel comes from the set of values taken by this…
Automated Detection of Optic Disc Location in Retinal Images
2008
This contribution presents an automated method to locate the optic disc in color fundus images. The method uses texture descriptors and a regression based method in order to determine the best circle that fits the optic disc. The best circle is chosen from a set of circles determined with an innovative method, not using the Hough transform as past approaches. An evaluation of the proposed method has been done using a database of 40 images. On this data set, our method achieved 95% success rate for the localization of the optic disc and 70% success rate for the identification of the optic disc contour (as a circle).
A Note about Eigenvalues, SVD and PCA
2013
Notes on eigen-decomposition, PCA, SVD and connexions.