Feature Extraction And Recognition Of Important Targets In Remote Sensing Imagery

Remote sensing imagery has great importance for military reconnaissance, precision attack and civil activities, so it has good application prospect to study feature extraction and target recognition methods of remote sensing imagery. This dissertation investigate the feature extraction and target recognition methods for blob targets, array targets and ports, and focus our research work mainly on their characters in structure and spatial relationship.Chapter 1 is the preface of this dissertation, which introduces the background knowledge, reviews the main content and the state of arts development of the feature extraction and target recognition in remote sensing imagery, and summarizes the central research work and innovative points in the dissertation.Chapter 2 studies the extraction and selection of texture features and the evaluation of texture feature discrimination performance (TFDP). The central work of this chapter includes: (1)reviewing the eight kinds of texture feature extraction methods currently used and the previous work in the evaluation of TFDP; (2)presenting a new texture feature extraction method using Local Walsh Transform (LWT), giving the definition of LWT and generalizing it in spatial domain, analyzing the statistic property of LWT coefficients, examining the TFDP of the central moments of LWT coefficients, and selecting the 2nd,4th,6th order moments which have better TFDP as texture features; (3) comparing our texture feature extraction method with the other eight methods in TFDP, texture image segmentation effect and computational complexity, which indicates that our method has the best performance; (4)presenting a new method based on LWT to segment sea area in optical remote sensing imagery, which integrates the characters of sea area in texture and structure.Chapter 3 studies the detection of blob targets. This chapter presents a novel algorithm based on visual attention model to detect blob targets in optical and infrared images. The blob targets have multi-feature and multi-scale difference as compared with their backgrounds, which is used by the visual attention model to locate the blob targets in the scenes. Farther on, scale salience is used to extract the region of the blob targets. The salience map computation procedure is modified. As a result, the salience map has higher spatial resolution and lower computation complexity, which make it more suitable to detection blob targets. Experiments reveal that our algorithm is immune to the distortion of images and targets, it can detect several classes of blob targets from scenes with considerable clutters.Chapter 4 studies the feature extraction and target recognition methods of array targets. The central work of this chapter includes: (1)presenting a practical scheme for feature extraction and target recognition based on the characters of array targets; (2) giving the definition of spatial relationship primitive(SRP), and presenting an effectiveSRP selection algorithm to make the full graph sparse; (3) presenting a spatial relationship regularity measure for arbitrary two SRPs based on Fuzzy theory; (4) establishing a full graph, namely Scene Structure Graph (SSG), and testifying some important properties of the adjacency matrix of the SSG, designing a fast spectral graph partitioning algorithm, namely Iterative Spectral Graph Partitioning Algorithm; (5) studying the recognition of oil tanks, missile positions and flack positions in remote sensing imagery using the algorithms presented above, which acquires promising recognition results.Chapter 5 studies the feature extraction and target recognition methods of port. This chapter treats port as a segment of coastline with special structure, detects and recognizes it by the way of analyzing the shape of coastline. The central works of this chapter includes: (1)bringing forward a new elasticity force computing method and a new extent force computing method to improve the performance of the traditional active contour model, and designing a high accurate coastline detection method using the improved active contour model; (2)giving out an effective inner port coastline extraction algorithm based on eigencluster technology; (3)presenting a port recognition algorithm using feature points relaxation matching method.Chapter 6 summarizes the dissertation and brings forward some problems which need further investigating.