Automatic segmentation of high resolution satellite (HRS) imagery is the first step and a very important part of object-oriented
approaches. The HRS sensors increase the spectral within-field heterogeneity and the structural or spatial details
of images. Spatial features are important to HRS image analysis in addition to spectral information. This paper presents a
novel feature extraction method and evaluates its performance on segmentation of HRS images based on adaptively
integrating multiple features. The first two principal component (PC) images are obtained by principal component
analysis (PCA) of a multispectral image and used to calculate the texture and spectral distributions of a region, which are
denoted by two-dimensional (2D) histograms. The 2D texture histogram of a region is the joint distribution of its two
texture labeled images calculated by rotation invariant local binary pattern (LBP) operator. The spectral distribution of a
region is the joint distribution of the pixel values of its two PC images after normalization. The color feature is a 2D
hue/saturation histogram that is computed through IHLS color space. The three features are integrated by a weighted sum
similarity measure and used to hierarchical splitting, modified agglomerative merging and boundary refinement
segmentation framework. The segmentation scheme based on adaptively integrating multiple features demonstrates
promising results.
With the rapid development of earth observation missions and internet technology, there is increasing recognition that
internet is an effective channel for disseminating digital remotely sensed data. To cope with the security problems
accompanying with internet-based remote sensing, a multipurpose watermarking technique of remote sensing images is
proposed in this paper for copyright protection and authentication in the spatial domain and the wavelet domain. The
proposed scheme can utilize the human visual system (HVS) to embed the copyright watermark in discrete wavelet
transform (DWT) medium frequency coefficients of the host image by permuting the watermark image, and embed the
authentication watermark in spatial domain to detect and indicate the counterfeit area clearly. It determines the location
where the watermark can be hidden and modifies the strength of the embedded watermark adaptively based on images
content. Furthermore, there is little influence on such application of remote sensing images as edge detection after
embedding watermarks.
An orthophoto pair has the property of zero-stereo and a stereo-orthophoto pair can be used for accurate elevation measurement. Based on these two points, an automatic quality diagnosis for digital image matching is presented in this paper. The main idea of this method is that after automatic generation of orthophoto pair and stereo-orthophoto pair from the to be tested DEM, derived from the image matching, and original left and right images, an automatic measurement procedure will be done in order to determine the heights or the corrections of height. This automatic diagnosis system gives a quality control and points out the positions where the matching is a failure and needs operator interactive work. The final products are corrected DEM, digital orthophoto, and stereo-orthophoto pair. The correctness and feasibility of the suggested method are tested using aerial photographs, SPOT stereo images, and simulation data.
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