reduced feature set

This paper presents two-stage unsupervised terrain classification of fully polarimetric SAR data using Freeman and Durden decomposition based on three simple scattering mechanisms: surface, volume and double bounce (first step), and textural features (uncorrelated uniformity, contrast, inverse moment and entropy) obtained from grey level co-occurrence matrices (GLCM) (second step). Textural features are defined in moving window 5x5 pixels with N=32 (N – number of grey levels). This algorithm preserves the purity of dominant polarimetric scattering properties and defines textural features in each scattering category. It is shown better object discrimination after applying texture within fixed scattering category. Speckle reduction is one of the main moments in image interpretation improvement because of its great influence on texture. Results from unfiltered and Lee filtered polarimetric SAR images show that the values of contrast and entropy decrease and the values of uniformity and inverse moment increase with speckle reduction, that’s true for all polarizations (HH, VV, HV). The discrimination between objects increases after speckle filtering. Polarization influence on texture features is defined by calculating the features in SAR images with HH, VV and HV polarizations before and after speckle filtering, and then creating RGB images. It is shown more polarization influence on texture features (uniformity, inverse moment and entropy) before filtering and less influence – after speckle filtering. It’s not true for contrast where polarization influence is not changed practically with filtering. SIR-C/X-SAR SLC L-band images of Moscow region are used for illustration. 1

completely different failure mode than that on the socketed CDM and real-world failures. Based on this work, a combined socketed and non-socketed CDM test approach is proposed for classifying/evaluating new products and driving CDM robustness improvements.

The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new

Abstract—As an object moves through the field of view of a camera, the images of the object may change dramatically. This is not simply due to the translation of the object across the image plane. Rather, complications arise due to the fact that the object undergoes changes in pose relative

Abstract—The goal of this work is to accurately detect and localize boundaries in natural scenes using local image measurements. We formulate features that respond to characteristic changes in brightness, color, and texture associated with natural boundaries. In order to combine the information

In a previous work ("Abstract Data Type Systems", TCS 173(2), 1997), the leI two authors presented a combined lmbined made of a (strongl normal3zG9 alrmal rewrite system and a typed #-calA#Ik enriched by pattern-matching definitions folnitio a certain format,calat the "

The TREC-3 project at Virginia Tech focused on methods for combining the evidence from multiple retrieval runs and queries to improve retrieval performance over any single retrieval method or query. The largest improvements result from the combination of retrieval paradigms rather than from the use

Abstract — This paper presents a simple two-branch transmit diversity scheme. Using two transmit antennas and one receive antenna the scheme provides the same diversity order as maximal-ratio receiver combining (MRRC) with one transmit antenna, and two receive antennas. It is also shown

ABSTRACT: This paper examines eight published reviews each reporting results from several related trials. Each review pools the results from the relevant trials in order to evaluate the efficacy of a certain treatment for a specified medical condition. These reviews lack consistent assessment