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We describe the distributed storage structure which can be effectively applied to scientific multidimensional imagery data in geoinformatics. Basic principal of this project is distributed (N,K)-block storage schema (LH*RS or SDDS). We develop the descent of LH*RS especially for multidimensional data arrays using the multiscaled representation of these arrays and using the efficient preprocessing...
Authors describe the novel approach for the data storing schema for fault-tolerant distributed scientific research systems. This approach optimizes the workload on storage nodes and enhances the computation performance. Basic principal of this project is distributed (N, K)-block storage schema (LH∗RS or SDDS) which makes the pre-computed hierarchic storage which can be efficient for some scientific...
In this research work a novel color correction algorithm for enhancing the color of digital images captured from low resolution cell phone cameras is proposed here. The procedure involves capturing images using various cell phones like Samsung, Nokia and Lenova having resolution of 2 mega pixels, 3 mega pixels and 5 mega pixels respectively. The scope of the work includes image acquisition using cell...
This paper describes an approach that improves the functionality of LH*RS - high-availability scalable distributed data structure. The core concept behind this approach is the particular implementation of LH* schema that allows efficient imagery data storage for online social networks to be created. We propose the novel wavelet-based method of buckets composition and distribution among storage nodes...
This paper aims to show an outline of Contourlet and Wavelet transforms, the main characteristics of them and subsequently exposed methodological form that was used in the development of experimental procedures were performed, finally presents the results obtained with the application of method of image fusion technique using satellite ARSIS for Contourlet and fast transform Wavelet Haar (FHWT).
The cancer is the second cause of death in Venezuela. In Lara State, the malign tumors of the digest organs, including the colorectal area, represent the 4.13% of the registered death. The specialists ensure that early detection of this disease increases the probability of healing. This paper presents a collection of algorithms developed for the automatic analysis of endoscopic color images of tissues...
Recently, image denoising using the wavelet transform has been attracting much attention. Wavelet based approach provides a particularly useful method for image denoising when the preservation of image features in the scene is of importance. In this paper, we propose a novel denoising method for removing additive noise present in the underwater images. In addition to scattering and absorption effects,...
Image segmentation is critical to image processing and pattern recognition, An image segmentation system is proposed for the segmentation of color image based on neural networks. First, we introduce BP Neural network, it has the capacity of parallel computing, distributed saving, self-studying, fault-to-learnt and nonlinear function approximating. So it widely used in image segmentation, but it also...
The local color cue based candidate boundary detection incorporating stationary Haar wavelet decomposition at various levels and thresholded proximity influence measures are used for detecting edges in color images in the proposed method. The non-homogeneous inter-tuples and non-uniform intra-tuple contributions of RGB tuples for conception of perceptual-edges are exploited in the edge detection method...
A variational model is proposed for color image fusion and contrast enhancement simultaneously. It combines the geometry of the images with the coherence and correlation constraints, the perceptual enhancement and the regularity constraints into a variational framework. The gradient descent flow is applied to minimize the functional and the numerical scheme of PDEs is presented. The model is compared...
An enhanced visualization algorithm for hyperspectral images (HSI) is presented in this paper. The visualization is based on the projection onto color matching functions of the human vision system. A contrast enhancement procedure is introduced making use of multiband gradient information. Both visualization and enhancement are combined into a multiresolution framework using wavelets. The HSI is transformed...
This paper presents a method for pavement crack detection, classification and evaluation using the Radon transform. The detection part of the algorithm is built upon the wavelet transform and the evaluation part is considered in the Radon transform domain. Since cracks have specific linear features in the space domain, the Radon transform can effectively be used on a binary image to classify and evaluate...
We present nonparametric methods for segmenting and classifying stem cell nuclei so as to enable the automatic monitoring of stem cell growth and development. The approach is based on combining level set methods, multiresolution wavelet analysis, and non-parametric estimation of the density functions of the wavelet coefficients from the decomposition. Additionally, to deal with small size textures...
We present a novel multiresolution analysis based stereo matching method using curvelets and modified adaptive support weight. Multiresolution analysis has long been applied to stereo correspondence. However, previous methods suffer from false matches arising from textureless region or repetitive textures and fattening effect due to area based matching. In the proposed approach, we have reduced false...
This paper introduces and comprehensively evaluates a new approach for classification of image regions. It is based on the so called wavelet standard deviation descriptor. Experiments performed for almost one thousand images with region segmentation given provided reasonable results for a very general application domain: “holiday pictures”.
The paper presents color texture segmentation using FCM for color texture segmentation based multi-resolution image fusion. First, a color texture images are decomposed of multi-resolution representation by wavelet transform, adaptive fusion weight value of wavelet coefficients are resolved using PCA, then fused images is formed by inverse transforming and combining all wavelet coefficients, the proposed...
This paper introduces the general process and characteristics of image fusion, investigates common algorithms of pixel level fusion by comparing five basic methods of the image fusion. The pixel level fusion experiments of the multispectral image and panchromatic image are performed by using the five methods. Finally, we analysis the experimental result, more detailed information of wavelet and IHS...
This paper explores the use of multi-bit quantisation of image features for similarity-based image retrieval. Our work builds on multi-resolution image similarity search algorithms which utilise one-bit representation of the largest magnitude wavelet coefficients. Given a query, images are ranked based on the number of quantised coefficients they have in common with the query. We explore the benefits...
This paper describes a novel method for detecting vehicles on a highway using two visual features: color and texture. Our method consists of a segmentation process computed on the L*u*v* color space and a texture feature extraction procedure based on Dual-Tree Complex Wavelet Transform. We also apply a denoising process using morphological operations to build a background model and make possible the...
This paper proposes an accurate reversible algorithm to convert full color images to gray images with keeping chroma and spatial resolution. In our previous study, we proposed a reversible color-to-gray algorithm using the two-level Haar wavelet transform with a packet assignment technique. The authors improve the algorithm by devising a color embedding technique. The proposed algorithm distributes...
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