Network flow optimization for restoration of images.
Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses
The increased production of Reactive Oxygen Species (ROS) in plant leaf tissues is a hallmark of a plant's reaction to various environmental stresses. This paper describes an automatic segmentation method for scanned images of cucurbits leaves stained to visualise ROS accumulation sites featured by specific colour hues and intensities. The leaves placed separately in the scanner view field on a colour background are extracted by thresholding in the RGB colour space, then cleaned from petioles to...
Nonlinear image processing and filtering: A unified approach based on vertically weighted regression
A class of nonparametric smoothing kernel methods for image processing and filtering that possess edge-preserving properties is examined. The proposed approach is a nonlinearly modified version of the classical nonparametric regression estimates utilizing the concept of vertical weighting. The method unifies a number of known nonlinear image filtering and denoising algorithms such as bilateral and steering kernel filters. It is shown that vertically weighted filters can be realized by a structure...
Nuclei segmentation for computer-aided diagnosis of breast cancer
On a functional depending on curvature and edges
On a variational theory of image amodal completion
On the jump set of solutions of the total variation flow
On the optimality of a new class of 2D recursive filters
The purpose of this paper is to prove the minimum variance property of a new class of 2D, recursive, finite-dimensional filters. The filtering algorithms are derived from general basic assumptions underlying the stochastic modelling of an image as a 2D gaussian random field. An appealing feature of the proposed algorithms is that the image pixels are estimated one at a time; this makes it possible to save computation time and memory requirement with respect to the filtering procedures based on strip...
On the singular decomposition of matrices.
Optimal Adaptive Blur Identification of Noisy Images
Parallel implementation of local thresholding in Mitrion-C
Mitrion-C based implementations of three image processing algorithms: a look-up table operation, simple local thresholding and Sauvola's local thresholding are described. Implementation results, performance of the design and FPGA logic utilization are discussed.
Parametric logarithmic type image processing for contrast based auto-focus in extreme lighting conditions
While most of state-of-the-art image processing techniques were built under the so-called classical linear image processing, an alternative that presents superior behavior for specific applications comes in the form of Logarithmic Type Image Processing (LTIP). This refers to mathematical models constructed for the representation and processing of gray tones images. In this paper we describe a general mathematical framework that allows extensions of these models by various means while preserving...
Probabilistic mixture-based image modelling
During the last decade we have introduced probabilistic mixture models into image modelling area, which present highly atypical and extremely demanding applications for these models. This difficulty arises from the necessity to model tens thousands correlated data simultaneously and to reliably learn such unusually complex mixture models. Presented paper surveys these novel generative colour image models based on multivariate discrete, Gaussian or Bernoulli mixtures, respectively and demonstrates...
Pyramidal watershed segmentation algorithm for high-resolution remote sensing images using discrete wavelet transforms.
Quasiconvex relaxation of multidimensional control problems with integrands f(t, ξ, v)
We prove a general relaxation theorem for multidimensional control problems of Dieudonné-Rashevsky type with nonconvex integrands f(t, ξ, v) in presence of a convex control restriction. The relaxed problem, wherein the integrand f has been replaced by its lower semicontinuous quasiconvex envelope with respect to the gradient variable, possesses the same finite minimal value as the original problem, and admits a global minimizer. As an application, we provide existence theorems for the image registration...
Quasiconvex relaxation of multidimensional control problems with integrands f(t, ξ, v)
We prove a general relaxation theorem for multidimensional control problems of Dieudonné-Rashevsky type with nonconvex integrands f(t, ξ, v) in presence of a convex control restriction. The relaxed problem, wherein the integrand f has been replaced by its lower semicontinuous quasiconvex envelope with respect to the gradient variable, possesses the same finite minimal value as the original problem, and admits a global minimizer. As an application, we provide existence theorems for the image registration...
Recognition of atherosclerotic plaques and their extended dimensioning with computerized tomography angiography imaging
In this paper the authors raise the issue of automatic discrimination of atherosclerotic plaques within an artery lumen based on numerical and statistical thresholding of Computerized Tomography Angiographic (CTA) images and their advanced dimensioning as a support for preoperative vessel assessment. For the study, a set of tomograms of the aorta, as well as the ilio-femoral and femoral arteries were examined. In each case a sequence of about 130-480 images of the artery cutoff planes were analyzed...
Reconstruction of quadratic curves in 3-D from two or more perspective views.
Region of interest contrast measures
A survey of local image contrast measures is presented and a new contrast measure for measuring the local contrast of regions of interest is proposed. The measures validation is based on the gradual objective contrast decreasing on medical test images in both grayscale and color. The performance of the eleven most frequented contrast measures is mutually compared and their robustness to different types of image degradation is analyzed. Since the contrast measures can be both global, regional and...
RGB-D terrain perception and dense mapping for legged robots
This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used...