401 research outputs found
Multilayer Structured NMF for Spectral Unmixing of Hyperspectral Images
One of the challenges in hyperspectral data analysis is the presence of mixed
pixels. Mixed pixels are the result of low spatial resolution of hyperspectral
sensors. Spectral unmixing methods decompose a mixed pixel into a set of
endmembers and abundance fractions. Due to nonnegativity constraint on
abundance fraction values, NMF based methods are well suited to this problem.
In this paper multilayer NMF has been used to improve the results of NMF
methods for spectral unmixing of hyperspectral data under the linear mixing
framework. Sparseness constraint on both spectral signatures and abundance
fractions matrices are used in this paper. Evaluation of the proposed algorithm
is done using synthetic and real datasets in terms of spectral angle and
abundance angle distances. Results show that the proposed algorithm outperforms
other previously proposed methods.Comment: 4 pages, conferenc
On-Line Object Feature Extraction for Multispectral Scene Representation
This thesis investigates a new on-line unsupervised object-feature extraction method that reduces the complexity and costs associated with the analysis of the multispectral image data and the data transmission, storage, archival and distribution as well. Typically in remote sensing a scene is represented by the spatially disjoint pixel-oriented features. It would appear possible to reduce data redundancy by an on-line unsupervised object-feature extraction process, where combined spatial-spectral object\u27s features, rather than the original pixel-features, are used for multispectral scene representation. The ambiguity in the object detection process can be reduced if the spatial dependencies, which exist among the adjacent pixels, are intelligently incorporated into the decision making process. We define the unity relation that must exist among the pixels of an object. The unity relation can be constructed with regard to the: adjacency relation, spectral-feature and spatial-feature characteristics in an object; e.g. AMICA (Automatic Multispectral Image Compaction Algorithm) uses the within object pixel feature gradient vector as a valuable contextual information to construct the object\u27s features, which preserve the class separability information within the data. For on-line object extraction, we introduce the path-hypothesis, and the basic mathematical tools for its realization are introduced in terms of a specific similarity measure and adjacency relation. AMICA is an example of on-line preprocessing algorithm that uses unsupervised object feature extraction to represent the information in the multispectral image data more efficiently. As the data are read into the system sequentially, the algorithm partitions the observation space into an exhaustive set of disjoint objects simultaneously with the data acquisition process, where, pixels belonging to an object form a path-segment in the spectral space. Each path-segment is characterized by an object-feature set. Then, the set of object-features, rather than the original pixel-features, is used for data analysis and data classification. AMICA is applied to several sets of real image data, and the performance and reliability of features is evaluated. Example results show an average compaction coefficient of more than 20/1 (this factor is data dependent). The classification performance is improved slightly by using object-features rather than the original data, and the CPU time required for classification is reduced by a factor of more than 20 as well. The feature extraction process may be implemented in real time, thus the object-feature extraction CPU time is neglectable; however, in the simulated satellite environment the CPU time for this process is less than 15% of CPU time for original data classification
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Tyrosine-Based Signals Regulate the Assembly of Dapleâ‹…PARD3 Complex at Cell-Cell Junctions.
Polarized distribution of organelles and molecules inside a cell is vital for a range of cellular processes and its loss is frequently encountered in disease. Polarization during planar cell migration is a special condition in which cellular orientation is triggered by cell-cell contact. We demonstrate that the protein Daple (CCDC88C) is a component of cell junctions in epithelial cells which serves like a cellular "compass" for establishing and maintaining contact-triggered planar polarity. Furthermore, these processes may be mediated through interaction with the polarity regulator PARD3. This interaction, mediated by Daple's PDZ-binding motif (PBM) and the third PDZ domain of PARD3, is fine-tuned by tyrosine phosphorylation on Daple's PBM by receptor and non-receptor tyrosine kinases, such as Src. Hypophosphorylation strengthens the interaction, whereas hyperphosphorylation disrupts it, thereby revealing an unexpected role of Daple as a platform for signal integration and gradient sensing for tyrosine-based signals within the planar cell polarity pathway
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