\Dimensionality" has recently been shown to be an important property in image measurement and image processing operators. It is often thought that morphological operations on an image with \volumic" (non-at) structuring elements lead to the breakdown of dimensionality. After a brief review of a new morphological scale-space, we show here that any dimensional functional of the scale-space image ...

We present a new algorithm for sub-bucket resolution segment positioning based on multiscale matched ltering of the Hough transform. It exhibits satisfactory performance even in the presence of noise and does not depend on feature width, thus being attractive for many image processing applications.

In this research, first of all, the existing problems in fragmentation measurement are reviewed for the sake of its fast and reliable evaluation. Then, the available methods used for evaluation of blast results are mentioned. The produced errors especially in recognizing the rock fragments in computer-aided methods, and also, the importance of determination of their sizes in the image analysis ...

The 2-D pyramidal image decomposition has been widely used in various image processing applications [6]. In this paper, we introduce filter bank implementations of a nonlinear multiresolution image representation based on local contrast measure. Following the work of Duval-Destin [3, 1] for visual contrast sensitivity, we define multiscale contrast coefficients by scaling the wavelet transform ...

Automatic image segmentation is emerging field in image processing research domain. Many researchers have developed various techniques for segmenting the interested region in an image. Saliency based image segmentation is one of the keen area of research. In a visual scene, the objects which are different from their surroundings get more visual importance and get high gaze attention of the view...

The saliency driven multiscale nonlinear diffusion filtering resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, inhabits and clear clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the ...

A multiscale approach to hyperspectral image data analysis using fractal signatures was proposed and implemented in the Interactive Data Language (IDL). For 2-D hyperspectral curves, fractal signature measures the changes in curve length with changing scale. Using NASA’s Earth Observing-1 (EO-1) Hyperion image from a study area near Denton, Texas, USA, the capabilities of fractal signatures in ...

We propose a unified framework for representing and processing images using a feature space related to local similarity. We choose the multiscale and versatile local jet feature space to represent the visual data. This feature space may be reduced by vector quantisation and/or be represented by data structures enabling efficient nearest neighbours search (e.g. kd-trees). We show the interest of...

Multiscale image registration techniques are presented for the registration of medical images using deformable registration models. The techniques are particularly effective for registration problems in which one or both of the images to be registered contains significant levels of noise. A brief overview of existing deformable registration techniques is presented, and experiments using B-splin...

since the birth of multi–spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray–scale images, instead of an ensemble of an n–d realization. although, even now, some researchers make the same assumption, it is proved that using vector geometries leads to better results. in this paper, first a method is proposed to extract th...