The paper describes a new method for extracting objects from high resolution color remote sensing images. This method is based on the fuzzy segmentation algorithm which has been developed in our previous works. The proposed object extraction method is following three steps. (1) Segmenting color images, (2) Detecting objects from segmented images, and (3) Postprocessing of extracted object. The ...

In this article, we proposed a novel image fusion method based on multiscale convolution sparse decomposition (MCSD). A unified framework MCSD is first utilized to decompose panchromatic (PAN) and the spatial component of upsampled low resolution multispectral (LR MS) images, which can produce corresponding frequencies feature maps. By combining with analysis, efficiently approximate spectral i...

High spatial resolution QuickBird satellite data have provided new opportunities for remote sensing applications in agriculture. In this study, image-based algorithms for atmospheric correction were evaluated on QuickBird imagery for retrieving surface reflectance (qk) of corn and potato canopies in Minnesota. The algorithms included the dark object subtraction technique (DOS), the cosine appro...

This article addresses the problem of urban street mapping from new high resolution satellite images. The proposed algorithm is divided in two sequential modules: a topologically correct graph of the street network is first extracted, and streets are then extracted as surface elements. The graph of the network is extracted by a following algorithm which minimizes a cost function. The surface ex...

Because of the combination of high spatial resolution and low spectral resolution associated with QuickBird imagery it is often difficult to apply traditional classification algorithms (which use spectral properties of individual image pixels) to derive thematic information, particularly in heterogeneous environments. Object-based approaches to classification, which attempt to describe relation...

The invasions of non-native species of vegetation pose significant threats to natural environments at all geographical scales. Saltcedar has been commonly treated as one of the several most threatening invasive species in U.S. in the next ten years. The spatial extent and density of infestation by saltcedar in the Rio Grande floodplain has been poorly understood in the past. Remote sensing prov...

Remote sensing represents a powerful tool to derive quantitative and qualitative information about ecosystem biodiversity. In particular, since plant species richness is a fundamental indicator of biodiversity at the community and regional scales, attempts were made to predict species richness (spatial heterogeneity) by means of spectral heterogeneity. The possibility of using spectral variance...

Classification is a crucial stage in the processing of satellite images that influence considerably quality result. A variety methods proposed literature for purposes image classification. They present many differences their basic principles, thus results obtained. Therefore, study different classification seems to be essential. The with conventional can done several ways using algorithms. Thes...

This paper presents a pansharpening technique based on the non-subsampled contourlet transform (NSCT) and convolutional autoencoder (CAE). NSCT is exceptionally proficient at presenting orientation information capturing internal geometry of objects. First, it’s used to decompose multispectral (MS) panchromatic (PAN) images into high-frequency low-frequency components using same number decomposi...