Metrics to evaluate compressions algorithms for RAW SAR data

Modern synthetic aperture radar (SAR) systems have size, weight, power and cost (SWAP-C) limitations since platforms are becoming smaller, while SAR operating modes are becoming more complex. Due to the computational complexity of the SAR processing required for modern SAR systems, performing the processing on board the platform is not a feasible option. Thus, SAR systems are producing an ever-increasing volume of data that needs to be transmitted to a ground station for processing. Compression algorithms are utilised to reduce the data volume of the raw data. However, these algorithms can cause degradation and losses that may degrade the effectiveness of the SAR mission. This study addresses the lack of standardised quantitative performance metrics to objectively quantify the performance of SAR data-compression algorithms. Therefore, metrics were established in two different domains, namely the data domain and the image domain. The data-domain metrics are used to determine the performance of the quantisation and the associated losses or errors it induces in the raw data samples. The image-domain metrics evaluate the quality of the SAR image after SAR processing has been performed. In this study three well-known SAR compression algorithms were implemented and applied to three real SAR data sets that were obtained from a prototype airborne SAR system. The performance of these algorithms were evaluated using the proposed metrics. Important metrics in the data domain were found to be the compression ratio, the entropy, statistical parameters like the skewness and kurtosis to measure the deviation from the original distributions of the uncompressed data, and the dynamic range. The data histograms are an important visual representation of the effects of the compression algorithm on the data. An important error measure in the data domain is the signal-to-quantisation-noise ratio (SQNR), and the phase error for applications where phase information is required to produce the output. Important metrics in the image domain include the dynamic range, the impulse response function, the image contrast, as well as the error measure, signal-to-distortion-noise ratio (SDNR). The metrics suggested that all three algorithms performed well and are thus well suited for the compression of raw SAR data. The fast Fourier transform block adaptive quantiser (FFT-BAQ) algorithm had the overall best performance, but the analysis of the computational complexity of its compression steps, indicated that it is has the highest level of complexity compared to the other two algorithms. Since different levels of degradation are acceptable for different SAR applications, a trade-off can be made between the data reduction and the degradation caused by the algorithm. Due to SWAP-C limitations, there also remains a trade-off between the performance and the computational complexity of the compression algorithm.Dissertation (MEng)--University of Pretoria, 2019.Electrical, Electronic and Computer EngineeringMEngUnrestricte

Intra-Key-Frame Coding and Side Information Generation Schemes in Distributed Video Coding

In this thesis investigation has been made to propose improved schemes for intra-key-frame coding and side information (SI) generation in a distributed video coding (DVC) framework. From the DVC developments in last few years it has been observed that schemes put more thrust on intra-frame coding and better quality side information (SI) generation. In fact both are interrelated as SI generation is dependent on decoded key frame quality. Hence superior quality key frames generated through intra-key frame coding will in turn are utilized to generate good quality SI frames. As a result, DVC needs less number of parity bits to reconstruct the WZ frames at the decoder. Keeping this in mind, we have proposed two schemes for intra-key frame coding namely, (a) Borrows Wheeler Transform based H.264/AVC (Intra) intra-frame coding (BWT-H.264/AVC(Intra)) (b) Dictionary based H.264/AVC (Intra) intra-frame coding using orthogonal matching pursuit (DBOMP-H.264/AVC (Intra)) BWT-H.264/AVC (Intra) scheme is a modified version of H.264/AVC (Intra) scheme where a regularized bit stream is generated prior to compression. This scheme results in higher compression efficiency as well as high quality decoded key frames. DBOMP-H.264/AVC (Intra) scheme is based on an adaptive dictionary and H.264/AVC (Intra) intra-frame coding. The traditional transform is replaced with a dictionary trained with K-singular value decomposition (K-SVD) algorithm. The dictionary elements are coded using orthogonal matching pursuit (OMP). Further, two side information generation schemes have been suggested namely, (a) Multilayer Perceptron based side information generation (MLP - SI) (b) Multivariable support vector regression based side information generation (MSVR-SI) MLP-SI scheme utilizes a multilayer perceptron (MLP) to estimate SI frames from the decoded key frames block-by-block. The network is trained offline using training patterns from different frames collected from standard video sequences. MSVR-SI scheme uses an optimized multi variable support vector regression (M-SVR) to generate SI frames from decoded key frames block-by-block. Like MLP, the training for M-SVR is made offline with known training patterns apriori. Both intra-key-frame coding and SI generation schemes are embedded in the Stanford based DVC architecture and studied individually to compare performances with their competitive schemes. Visual as well as quantitative evaluations have been made to show the efficacy of the schemes. To exploit the usefulness of intra-frame coding schemes in SI generation, four hybrid schemes have been formulated by combining the aforesaid suggested schemes as follows: (a) BWT-MLP scheme that uses BWT-H.264/AVC (Intra) intra-frame coding scheme and MLP-SI side information generation scheme. (b) BWT-MSVR scheme, where we utilize BWT-H.264/AVC (Intra) for intra-frame coding followed by MSVR-SI based side information generation. (c) DBOMP-MLP scheme is an outcome of putting DBOMP-H.264/AVC (Intra) intra-frame coding and MLP-SI side information generation schemes. (d) DBOMP-MSVR scheme deals with DBOMP-H.264/AVC (Intra) intra-frame coding and MSVR-SI side information generation together. The hybrid schemes are also incorporated into the Stanford based DVC architecture and simulation has been carried out on standard video sequences. The performance analysis with respect to overall rate distortion, number requests per SI frame, temporal evaluation, and decoding time requirement has been made to derive an overall conclusion

Data transmission oriented on the object, communication media, application, and state of communication systems tactical communication system application

A proposed communication system architecture is denoted TOMAS, which stands for data Transmission oriented on the Object, communication Media, Application, and state of communication Systems. Given particular tactical communication system scenarios of image transmission over a wireless LOS (Line-of-Sight) channel, a wireless TOMAS system demonstrates superior performance compared to the conventional system, which is a combination of JPEG2000 image compression and OFDM transmission, in restored image quality parameters over a wide range of wireless channel parameters. The wireless TOMAS system provides progressive lossless image transmission under the influence of moderate fading without any kind of channel coding and estimation. The TOMAS system employs a fast proprietary patent pending algorithm Sabelkin (2011), which does not employ any multiplications, and it uses three times less real additions than the algorithm of JPEG2000+OFDM. The TOMAS system exploits a specialized wavelet transform combined for image coding and channel modulation

Metrics to evaluate compressions algorithms for RAW SAR data

Modern synthetic aperture radar (SAR) systems have size, weight, power and cost (SWAP-C) limitations since platforms are becoming smaller, while SAR operating modes are becoming more complex. Due to the computational complexity of the SAR processing required for modern SAR systems, performing the processing on board the platform is not a feasible option. Thus, SAR systems are producing an ever-increasing volume of data that needs to be transmitted to a ground station for processing. Compression algorithms are utilised to reduce the data volume of the raw data. However, these algorithms can cause degradation and losses that may degrade the effectiveness of the SAR mission. This study addresses the lack of standardised quantitative performance metrics to objectively quantify the performance of SAR data-compression algorithms. Therefore, metrics were established in two different domains, namely the data domain and the image domain. The data-domain metrics are used to determine the performance of the quantisation and the associated losses or errors it induces in the raw data samples. The image-domain metrics evaluate the quality of the SAR image after SAR processing has been performed. In this study three well-known SAR compression algorithms were implemented and applied to three real SAR data sets that were obtained from a prototype airborne SAR system. The performance of these algorithms were evaluated using the proposed metrics. Important metrics in the data domain were found to be the compression ratio, the entropy, statistical parameters like the skewness and kurtosis to measure the deviation from the original distributions of the uncompressed data, and the dynamic range. The data histograms are an important visual representation of the effects of the compression algorithm on the data. An important error measure in the data domain is the signal-to-quantisation-noise ratio (SQNR), and the phase error for applications where phase information is required to produce the output. Important metrics in the image domain include the dynamic range, the impulse response function, the image contrast, as well as the error measure, signal-to-distortion-noise ratio (SDNR). The metrics suggested that all three algorithms performed well and are thus well suited for the compression of raw SAR data. The fast Fourier transform block adaptive quantiser (FFT-BAQ) algorithm had the overall best performance, but the analysis of the computational complexity of its compression steps, indicated that it is has the highest level of complexity compared to the other two algorithms. Since different levels of degradation are acceptable for different SAR applications, a trade-off can be made between the data reduction and the degradation caused by the algorithm. Due to SWAP-C limitations, there also remains a trade-off between the performance and the computational complexity of the compression algorithm.Dissertation (MEng)--University of Pretoria, 2019.TM2019Electrical, Electronic and Computer EngineeringMEngUnrestricte

Image Processing Using FPGAs

This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs

Impact perceptuel d'une mise à zéro des segments plosifs de parole

En traitement du signal audio, les plosives sont des sons de parole très importants au regard de l’intelligibilité et de la qualité. Les plosives sont cependant difficiles à modéliser à l’aide des techniques usuelles (prédiction linéaire et codage par transformée), à cause de leur dynamique propre importante et à cause de leur nature non prédictible. Cette étude présente un exemple de système complet capable de détecter, segmenter, et altérer les plosives dans un flux de parole. Ce système est utilisé afin de vérifier la validité de l’hypothèse suivante : La phase d’éclatement (de burst) des plosives peut être mise à zéro, de façon perceptuellement équivalente. L’impact sur la qualité subjective de cette transformation est évalué sur une banque de phrases enregistrées. Les résultats de cette altération hautement destructive des signaux tendent à montrer que l’impact perceptuel est mineur. Les implications de ces résultats pour le codage de la parole sont abordées

Application of Asynchronous Transfer Mode (Atm) technology to Picture Archiving and Communication Systems (Pacs): A survey

Broadband Integrated Services Digital Network (R-ISDN) provides a range of narrowband and broad-band services for voice, video, and multimedia. Asynchronous Transfer Mode (ATM) has been selected by the standards bodies as the transfer mode for implementing B-ISDN; The ability to digitize images has lead to the prospect of reducing the physical space requirements, material costs, and manual labor of traditional film handling tasks in hospitals. The system which handles the acquisition, storage, and transmission of medical images is called a Picture Archiving and Communication System (PACS). The transmission system will directly impact the speed of image transfer. Today the most common transmission means used by acquisition and display station products is Ethernet. However, when considering network media, it is important to consider what the long term needs will be. Although ATM is a new standard, it is showing signs of becoming the next logical step to meet the needs of high speed networks; This thesis is a survey on ATM, and PACS. All the concepts involved in developing a PACS are presented in an orderly manner. It presents the recent developments in ATM, its applicability to PACS and the issues to be resolved for realising an ATM-based complete PACS. This work will be useful in providing the latest information, for any future research on ATM-based networks, and PACS