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This paper presents an extensible skew window for a multi-pixel inputs that enable parallel labeling. The corresponding 1 × 3 masks stack as a skew window based on the number of input pixels that require labeling. Based on the skew window and two pass processing, we developed a parallel labeling algorithm for assigning and merging parallel labels. To obtain tentative labels on the first pass, the...
We introduce the hierarchical Markov aspect model (HMAM), a computationally efficient graphical model for densely labeling large remote sensing images with their underlying terrain classes. HMAM resolves local ambiguities efficiently by combining the benefits of quadtree representations and aspect models—the former incorporate multiscale visual features and hierarchical smoothing to provide improved...
In this paper, we present a fast approach to obtain semantic scene segmentation with high precision. We employ a two-stage classifier to label all image pixels. First, we use the regularized logistic regression to combine different appearance-based features and the improved spatial layout of labeling information. In the second stage, we incorporate the local, regional and global cues into a conditional...
The paper proposes a fast and accurate semantic segmentation approach for a large Polarimetric SAR (PolSAR) image using Conditional Random Fields (CRFs). It efficiently incorporates the polarimetric signatures, texture and intensity features into a unite CRFs model, and employs a fast max-margin training method for parameters learning. Experiments on RadarSat-2 PolSAR data in Flevoland test site demonstrate...
In this paper, we present a parallel connected component labeling method and its VLSI architecture design. The proposed method can assign labels to three pixels simultaneously for the raster scan input and then generate three label equivalences rapidly. We also present 3 arrays to process all label mergence. Based on the proposed method, we develop the hardware design for realtime application. The...
In this study, we are going to focus on the exploration of color based features on labeling remote sensing images. The common widely used color descriptors are based on color histogram or Gaussian Mixture Models. However, the problem of these methods is to lack of the spatial layout information. We propose a new color description and matching approach, which allows to relax the assumption of independence...
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