Optimum Feature Selection For Classfication of Lidar Data Using Genetic Algorithms2. Genetic Search Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution. The main operator of genetic algorithm to search in pool of possible solutions is Crossover, Mutation and Elitism. The usual approach to the use of GAs for feature selection involves encoding a set of d features as a binary string of d elements, in which a 0 in the string indicates that the corresponding feature is to be omitted, and a 1 that it is to be included this coding scheme represent the presence or absence of a particular feature from the feature space Figure (1). the length of chromosome equal to feature space dimension.  Figure 1. Designed Chromosome for subset Selection 3. Maximum Likelihood Classifier Classification can be defined as the association of a land use/land cover attribute to every pixels of an image (Duda and P.E. Hart-1973), and ML Supervised image classification begins with computing statistics for user-selected training feature vector of land cover classes and it uses the results of the statistical summary to classify the image. For classify the image, the probabilities of each feature vector’s belonging to each of the classes are calculated and the image pixel is assigned to the class for which this probability is the highest. The computation of probabilities is given by:  ...................(1)Where μ is the mean value and ∑ is the covariance matrix of class i Gi(x)> Gj(x)if then pixel x is belong to class i. 4. Data set The airborne LIDAR data used in the experimental investigations have been recorded from city in Germany. The pixel size of the range images is one meter per pixel so that the density of point is one per m2. Intensity images for the first and last pulse data have been also recorded and the intention was to use them too in the experimental investigations. Furthermore colored aerial image was available for describe spectral property of objects. Feature space has 8 members in which constitute a subcategory .a pool of possible feature or feature spaces contain:
 ...............(2) Figure 2.Range Image First & Range Image last |