Sparse Coding Based Feature Representation Method for Remote Sensing Images

In this dissertation, we study sparse coding based feature representation method for the classification of multispectral and hyperspectral images (HSI). The existing feature representation systems based on the sparse signal model are computationally expensive, requiring to solve a convex optimization problem to learn a dictionary. A sparse coding feature representation framework for the classification of HSI is presented that alleviates the complexity of sparse coding through sub-band construction, dictionary learning, and encoding steps. In the framework, we construct the dictionary based upon the extracted sub-bands from the spectral representation of a pixel. In the encoding step, we utilize a soft threshold function to obtain sparse feature representations for HSI. Experimental results showed that a randomly selected dictionary could be as effective as a dictionary learned from optimization. The new representation usually has a very high dimensionality requiring a lot of computational resources. In addition, the spatial information of the HSI data has not been included in the representation. Thus, we modify the framework by incorporating the spatial information of the HSI pixels and reducing the dimension of the new sparse representations. The enhanced model, called sparse coding based dense feature representation (SC-DFR), is integrated with a linear support vector machine (SVM) and a composite kernels SVM (CKSVM) classifiers to discriminate different types of land cover. We evaluated the proposed algorithm on three well known HSI datasets and compared our method to four recently developed classification methods: SVM, CKSVM, simultaneous orthogonal matching pursuit (SOMP) and image fusion and recursive filtering (IFRF). The results from the experiments showed that the proposed method can achieve better overall and average classification accuracies with a much more compact representation leading to more efficient sparse models for HSI classification. To further verify the power of the new feature representation method, we applied it to a pan-sharpened image to detect seafloor scars in shallow waters. Propeller scars are formed when boat propellers strike and break apart seagrass beds, resulting in habitat loss. We developed a robust identification system by incorporating morphological filters to detect and map the scars. Our results showed that the proposed method can be implemented on a regular basis to monitor changes in habitat characteristics of coastal waters

Remote Sensing Data Compression

A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired or necessary. A wide diversity of coding methods can be used, depending on the requirements and their priority. In addition, the types and properties of images differ a lot, thus, practical implementation aspects have to be taken into account. The Special Issue paper collection taken as basis of this book touches on all of the aforementioned items to some degree, giving the reader an opportunity to learn about recent developments and research directions in the field of image compression. In particular, lossless and near-lossless compression of multi- and hyperspectral images still remains current, since such images constitute data arrays that are of extremely large size with rich information that can be retrieved from them for various applications. Another important aspect is the impact of lossless compression on image classification and segmentation, where a reasonable compromise between the characteristics of compression and the final tasks of data processing has to be achieved. The problems of data transition from UAV-based acquisition platforms, as well as the use of FPGA and neural networks, have become very important. Finally, attempts to apply compressive sensing approaches in remote sensing image processing with positive outcomes are observed. We hope that readers will find our book useful and interestin

Impedance spectroscopy for in vitro toxicology

The impedance of biological material changes with frequency, a phenomenon that has been discovered more than 100 years ago. It is due to the fact that the cell membrane acts as a capacitor which filters out currents at low frequency and lets them pass at high frequency. This fundamental knowledge about biological dielectrics has incompletely been exploited to detect and distinguish toxicity effects on cell cultures, although impedance measurements have been used for long in this field. In this thesis, it was found that low frequency impedance signals are linked to initial stress responses of cells within cell populations when exposed to a toxin whereas high frequency measurements inform about major cell damage as is indicated by intracellular conductivity changes. In addition, when cells gain resistance to a toxin, they experience a higher cell stiffness which is expressed by an increased low frequency impedance. The study of impedance changes as a function of frequency and drug concentrations lead to the creation of an impedimetric concentration-response map which distinguishes cell responses within four concentration ranges without the use of any label. Although being inherently non-specific, this measurement method was shown to report on distinct toxicity effects, an important prerequisite when studying drug action on cancer cells where stimulating and lethal effects need to be distinguished rigorously. This thesis further encompasses the subject of three-dimensional impedance measurements, i.e. the screening of the entire depth of a three-dimensional tissue culture. Given the success of impedance measurements on cell monolayers, one would expect this development to continue with 3D cultures since the complex structure of in vivo tissues is mimicked more closely and, above all, since rapid and inexpensive techniques which are able to probe thick tissue samples are currently inexistent. Nevertheless, few studies have been carried out in this field. Here, the requirements of three-dimensional impedance sensors are discussed and challenged by the fabrication of a corresponding device, involving the development of so-called gel electrodes through a novel 2-step-soft-lithography process. Their specific design allows for the decrease of leak currents, a common problem when performing three-dimensional impedance measurements. The simultaneous measurement of multiple samples in parallel is an an essential condition when performing high throughput drug toxicity screening. Electrode switch systems are necessary which ultimately lead to setup complexity and signal noises. In this thesis, a method is introduced, enabling the simultaneous implementation of impedance measurements of multiple tissue samples with one electrode pair only. This is simply achieved by exploiting the frequency domain and finally contributed to reducing setup complexity

Cumulative index to NASA Tech Briefs, 1986-1990, volumes 10-14

Tech Briefs are short announcements of new technology derived from the R&D activities of the National Aeronautics and Space Administration. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This cumulative index of Tech Briefs contains abstracts and four indexes (subject, personal author, originating center, and Tech Brief number) and covers the period 1986 to 1990. The abstract section is organized by the following subject categories: electronic components and circuits, electronic systems, physical sciences, materials, computer programs, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Proceedings of the Scientific-Practical Conference "Research and Development - 2016"

talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog

Applications and Experiences of Quality Control

The rich palette of topics set out in this book provides a sufficiently broad overview of the developments in the field of quality control. By providing detailed information on various aspects of quality control, this book can serve as a basis for starting interdisciplinary cooperation, which has increasingly become an integral part of scientific and applied research