Toward reduction of artifacts in fused images

Most fusion satellite image methodologies at pixel-level introduce false spatial details, i.e.artifacts, in the resulting fusedimages. In many cases, these artifacts appears because image fusion methods do not consider the differences in roughness or textural characteristics between different land covers. They only consider the digital values associated with single pixels. This effect increases as the spatial resolution image increases. To minimize this problem, we propose a new paradigm based on local measurements of the fractal dimension (FD). Fractal dimension maps (FDMs) are generated for each of the source images (panchromatic and each band of the multi-spectral images) with the box-counting algorithm and by applying a windowing process. The average of source image FDMs, previously indexed between 0 and 1, has been used for discrimination of different land covers present in satellite images. This paradigm has been applied through the fusion methodology based on the discrete wavelet transform (DWT), using the à trous algorithm (WAT). Two different scenes registered by optical sensors on board FORMOSAT-2 and IKONOS satellites were used to study the behaviour of the proposed methodology. The implementation of this approach, using the WAT method, allows adapting the fusion process to the roughness and shape of the regions present in the image to be fused. This improves the quality of the fusedimages and their classification results when compared with the original WAT metho

Application of Multifractal Analysis to Segmentation of Water Bodies in Optical and Synthetic Aperture Radar Satellite Images

A method for segmenting water bodies in optical and synthetic aperture radar (SAR) satellite images is proposed. It makes use of the textural features of the different regions in the image for segmentation. The method consists in a multiscale analysis of the images, which allows us to study the images regularity both, locally and globally. As results of the analysis, coarse multifractal spectra of studied images and a group of images that associates each position (pixel) with its corresponding value of local regularity (or singularity) spectrum are obtained. Thresholds are then applied to the multifractal spectra of the images for the classification. These thresholds are selected after studying the characteristics of the spectra under the assumption that water bodies have larger local regularity than other soil types. Classifications obtained by the multifractal method are compared quantitatively with those obtained by neural networks trained to classify the pixels of the images in covered against uncovered by water. In optical images, the classifications are also compared with those derived using the so-called Normalized Differential Water Index (NDWI)

Characterizing the structure of diffuse emission in Hi-GAL maps

We present a study of the structure of the Galactic interstellar medium through the Delta-variance technique, related to the power spectrum and the fractal properties of infrared/sub-mm maps. Through this method, it is possible to provide quantitative parameters which are useful to characterize different morphological and physical conditions, and to better constrain the theoretical models. In this respect, the Herschel Infrared Galactic Plane Survey carried out at five photometric bands from 70 to 500 \mu m constitutes an unique database for applying statistical tools to a variety of regions across the Milky Way. In this paper, we derive a robust estimate of the power-law portion of the power spectrum of four contiguous 2{\deg}x2{\deg} Hi-GAL tiles located in the third Galactic quadrant (217{\deg} < l < 225{\deg}, -2{\deg} < b < 0{\deg}). The low level of confusion along the line of sight testified by CO observations makes this region an ideal case. We find very different values of the power spectrum slope from tile to tile but also from wavelength to wavelength (2 < \beta < 3), with similarities between fields attributable to components located at the same distance. Thanks to the comparison with models of turbulence, an explanation of the determined slopes in terms of the fractal geometry is also provided, and possible relations with the underlying physics are investigated. In particular, an anti-correlation between ISM fractal dimension and star formation efficiency is found for the two main distance components observed in these fields. A possible link between the fractal properties of the diffuse emission and the resulting clump mass function is discussed.Comment: Accepted by Ap

A Genetic Bayesian Approach for Texture-Aided Urban Land-Use/Land-Cover Classification

Urban land-use/land-cover classification is entering a new era with the increased availability of high-resolution satellite imagery and new methods such as texture analysis and artificial intelligence classifiers. Recent research demonstrated exciting improvements of using fractal dimension, lacunarity, and Moran’s I in classification but the integration of these spatial metrics has seldom been investigated. Also, previous research focuses more on developing new classifiers than improving the robust, simple, and fast maximum likelihood classifier. The goal of this dissertation research is to develop a new approach that utilizes a texture vector (fractal dimension, lacunarity, and Moran’s I), combined with a new genetic Bayesian classifier, to improve urban land-use/land-cover classification accuracy. Examples of different land-use/land-covers using post-Katrina IKONOS imagery of New Orleans were demonstrated. Because previous geometric-step and arithmetic-step implementations of the triangular prism algorithm can result in significant unutilized pixels when measuring local fractal dimension, the divisor-step method was developed and found to yield more accurate estimation. In addition, a new lacunarity estimator based on the triangular prism method and the gliding-box algorithm was developed and found better than existing gray-scale estimators for classifying land-use/land-cover from IKONOS imagery. The accuracy of fractal dimension-aided classification was less sensitive to window size than lacunarity and Moran’s I. In general, the optimal window size for the texture vector-aided approach is 27x27 to 37x37 pixels (i.e., 108x108 to 148x148 meters). As expected, a texture vector-aided approach yielded 2-16% better accuracy than individual textural index-aided approach. Compared to the per-pixel maximum likelihood classification, the proposed genetic Bayesian classifier yielded 12% accuracy improvement by optimizing prior probabilities with the genetic algorithm; whereas the integrated approach with a texture vector and the genetic Bayesian classifier significantly improved classification accuracy by 17-21%. Compared to the neural network classifier and genetic algorithm-support vector machines, the genetic Bayesian classifier was slightly less accurate but more computationally efficient and required less human supervision. This research not only develops a new approach of integrating texture analysis with artificial intelligence for classification, but also reveals a promising avenue of using advanced texture analysis and classification methods to associate socioeconomic statuses with remote sensing image textures

Tissue multifractality and Born approximation in analysis of light scattering: a novel approach for precancers detection

Multifractal, a special class of complex self-affine processes, are under recent intensive investigations because of their fundamental nature and potential applications in diverse physical systems. Here, we report on a novel light scattering-based inverse method for extraction/quantification of multifractality in the spatial distribution of refractive index of biological tissues. The method is based on Fourier domain pre-processing via the Born approximation, followed by the Multifractal Detrended Fluctuation Analysis. The approach is experimentally validated in synthetic multifractal scattering phantoms, and tested on biopsy tissue slices. The derived multifractal properties appear sensitive in detecting cervical precancerous alterations through an increase of multifractality with pathology progression, demonstrating the potential of the developed methodology for novel precancer biomarker identification and tissue diagnostic tool. The novel ability to delineate the multifractal optical properties from light scattering signals may also prove useful for characterizing a wide variety of complex scattering media of non-biological origin

The 3-Dimensional Distribution of Dust in NGC 891

We produce three-dimensional Monte-Carlo radiative transfer models of the edge-on spiral galaxy NGC 891, a fast-rotating galaxy thought to be an analogue to the Milky Way. The models contain realistic spiral arms and a fractal distribution of clumpy dust. We fit our models to Hubble Space Telescope images corresponding to the B and I bands, using shapelet analysis and a genetic algorithm to generate 30 statistically best-fitting models. These models have a strong preference for spirality and clumpiness, with average face-on attenuation decreasing from 0.24(0.16) to 0.03(0.03) mag in the B(I) band between 0.5 and 2 radial scale-lengths. Most of the attenuation comes from small high-density clumps with low (<10%) filling factors. The fraction of dust in clumps is broadly consistent with results from fitting NGC 891's spectral energy distribution. Because of scattering effects and the intermixed nature of the dust and starlight, attenuation is smaller and less wavelength-dependent than the integrated dust column-density. Our clumpy models typically have higher attenuation at low inclinations than previous radiative transfer models using smooth distributions of stars and dust, but similar attenuation at inclinations above 70 degrees. At all inclinations most clumpy models have less attenuation than expected from previous estimates based on minimizing scatter in the Tully-Fisher relation. Mass-to-light ratios are higher and the intrinsic scatter in the Tully-Fisher relation is larger than previously expected for galaxies similar to NGC 891. The attenuation curve changes as a function of inclination, with R_(B,B-I)=A_(B)/E(B-I) increasing by ~0.75 from face-on to near-edge-on orientations.Comment: 26 pages, 18 figures, accepted for publication in Ap

Integration of Panchromatic and Multispectral Images by Local Fractal Dimension

The fusion image strategies are a good solution to obtain a synthetic image with high spatial and spectral characteristics simultaneously. Some of them are based on the Wavelet Transform, computed by means of the à trous algorithm (AWT). Most of them do not differentiated between spectral bands. In this sense, a new approach that weights differently the spatial information integrated from the high resolution image in each of the fused image spectral bands by the optimization of the trade off between the spatial and spectral quality of the fused images, was proposed. The main problems of this approach are that a unique weighting factor for the whole spectral band is computed, and the need of indices, that separately measure the spectral and spatial quality of the fused images. In this work, a new strategy that tries to avoid the problems above mentioned is introduced. For that, it is proposed to determine a local weighting factor for each panchromatic pixel by means the fractal map, using the box-counting algorithm. Panchromatic and multispectral Quickbird images have been used to show the performances of this new methodology. The local quality of the final fused images has been evaluated by means of local quality maps of Q index. It has been proved that the proposed fusion strategy preserve the high frequency information of the panchromatic image in areas with a high detail, while in homogeneous areas the low frequency information of the multispectral image are conserved