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27
A Survey on JPEG2000 Encryption
, 2009
"... Image and video encryption has become a widely discussed topic; especially for the fully featured JPEG2000 compression standard numerous approaches have been proposed. A comprehensive survey of state-of-the-art JPEG2000 encryption is given. JPEG2000 encryption schemes are assessed in terms of secur ..."
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Cited by 5 (4 self)
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Image and video encryption has become a widely discussed topic; especially for the fully featured JPEG2000 compression standard numerous approaches have been proposed. A comprehensive survey of state-of-the-art JPEG2000 encryption is given. JPEG2000 encryption schemes are assessed in terms of security, runtime and compression performance and their suitability for a wide range of application scenarios.
Adaptive Contextual Energy Parameterization for Automated Image Segmentation
"... Abstract. Image segmentation techniques are predominately based on parameter-laden optimization processes. The segmentation objective function traditionally involves parameters (i.e. weights) that need to be tuned in order to balance the underlying competing cost terms of image data fidelity and con ..."
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Cited by 4 (3 self)
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Abstract. Image segmentation techniques are predominately based on parameter-laden optimization processes. The segmentation objective function traditionally involves parameters (i.e. weights) that need to be tuned in order to balance the underlying competing cost terms of image data fidelity and contour regularization. In this paper, we propose a novel approach for automatic adaptive energy parameterization. In particular, our contributions are three-fold; 1) We spatially adapt fidelity and regularization weights to local image content in an autonomous manner. 2) We modulate the weight using a novel contextual measure of image quality based on the concept of spectral flatness. 3) We incorporate our proposed parameterization into a general segmentation framework and demonstrate its superiority to two alternative approaches: the best possible spatially-fixed parameterization and the globally optimal spatiallyvarying, but non-contextual, parameters. Our segmentation results are evaluated on real and synthetic data and produce a reduction in mean segmentation error when compared to alternative approaches. Key words: Adaptive regularization, contextual weights, image segmentation, energy minimization, adapting energy functional, spectral flatness, noise estimation 1
GPU-Based DWT Acceleration for JPEG2000
- ANNUAL DOCTORAL WORKSHOP ON MATHEMATICAL AND ENGINEERING METHODS IN COMPUTER SCIENCE
, 2009
"... Abstract. In our paper, we focus on accelerating DWT (Discrete Wavelet Transform) part of the JPEG2000 using general-purpose processing on graphical processing unit (GPU). We utilize Compute Unified Device Architecture (CUDA) platform which has its specific properties and constraints. In particular, ..."
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Cited by 3 (1 self)
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Abstract. In our paper, we focus on accelerating DWT (Discrete Wavelet Transform) part of the JPEG2000 using general-purpose processing on graphical processing unit (GPU). We utilize Compute Unified Device Architecture (CUDA) platform which has its specific properties and constraints. In particular, a proper memory treatment can greatly affect overall performance. In this paper, we briefly describe corresponding CUDA technical background followed by elaborated description of the algorithm—especially its memory layout part. Resulting implementation of DWT performs very well compared to other implementations available and is able to process an HD sized picture within 1 ms or faster. 1
GPU-Based Sample-Parallel Context Modeling for EBCOT in JPEG2000
- MEMICS 2010 PROCEEDINGS
, 2010
"... Abstract. Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. EBCOT itself consists of two tiers. In Tier-1, image samples are compressed using context modeling and arithme ..."
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Cited by 1 (0 self)
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Abstract. Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. EBCOT itself consists of two tiers. In Tier-1, image samples are compressed using context modeling and arithmetic coding. Resulting bit-stream is further formated and truncated in Tier-2. JPEG2000 has a number of applications in various fields where the processing speed and/or latency is a crucial attribute and the main limitation with state of the art implementations. In this paper we propose a new parallel approach to EBCOT context modeling that truly exploits massively parallel capabilities of modern GPUs and enables concurrent processing of individual image samples. Performance evaluation of our prototype shows speedup 12 times for the context modeller, and 1.4–5.3 times for the whole EBCOT Tier-1, which includes not yet optimized arithmetic coder. 1
images: the LAR compression framework
, 2012
"... Preserving data integrity of encoded medical ..."
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Title of Document: DETECTION AND CLASSIFICATION OF NON-STATIONARY SIGNALS USING SPARSE REPRESENTATIONS IN ADAPTIVE DICTIONARIES
"... Automatic classification of non-stationary radio frequency (RF) signals is of particular interest in persistent surveillance and remote sensing applications. Such signals are often acquired in noisy, cluttered environments, and may be characterized by complex or unknown analytical models, making fea ..."
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Automatic classification of non-stationary radio frequency (RF) signals is of particular interest in persistent surveillance and remote sensing applications. Such signals are often acquired in noisy, cluttered environments, and may be characterized by complex or unknown analytical models, making feature extraction and classification difficult. This thesis proposes an adaptive classification approach for poorly characterized targets and backgrounds based on sparse representations in non-analytical dictionaries learned from data. Conventional analytical orthogonal dictionaries, e.g., Short Time Fourier and Wavelet Transforms, can be suboptimal for classification of non-stationary signals, as they provide a rigid tiling of the time-frequency space, and are not specifically designed for a particular signal class. They generally do not lead to sparse decompositions (i.e., with very few non-zero coefficients), and use in classification requires separate feature selection algorithms. Pursuit-type decompositions in analytical overcomplete (non-orthogonal) dictionaries yield sparse representations, by design, and work well for signals that are similar to the dictionary elements. The pursuit search, however, has a high computational cost,
Preserving data integrity of encoded medical images: the LAR compression framework
, 2012
"... HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Preserving data integrity of encoded medical images: the LAR compression framework
EFFICIENT LOSSLESS COLOUR IMAGE CODING WITH SPECK
"... This paper proposes an efficient extension of Set Partitioning Embedded bloCK (SPECK) algorithm to lossless colour image coding by using the integer wavelet transform. First, the RGB image is losslessly transformed to LC (Luminance-Chrominance) plane. Then, an integer wavelet transform is applied to ..."
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This paper proposes an efficient extension of Set Partitioning Embedded bloCK (SPECK) algorithm to lossless colour image coding by using the integer wavelet transform. First, the RGB image is losslessly transformed to LC (Luminance-Chrominance) plane. Then, an integer wavelet transform is applied to each plane. Depending on the energy of each transformed plane and the correlation between each pair of planes, we select two planes to be grouped together into the List of Insignificant Sets LIS in SPECK algorithm in order to exploit the inter-redundancy of information so as to achieve a better performance of coding. The idea behind this is that the sets in LIS at the same location in two correlated planes with close energy are very likely to have the same information of significance with respect to a given threshold. Hence, joining them together can yield an important gain of the amount of bits. This novel method has been assessed in comparison to the separated one presented in [5] and the simulation results show a better performance of the proposed technique. 2.
Image Compression using Combined FIR-IIR Filters
"... The paper discussed suggests a new algorithm for image compression that combines the features useful of Finite impulse type and Infinite impulse type filters. The simulation results show that the new algorithm improves good compression ratio as it is needed for many advanced image processing applica ..."
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The paper discussed suggests a new algorithm for image compression that combines the features useful of Finite impulse type and Infinite impulse type filters. The simulation results show that the new algorithm improves good compression ratio as it is needed for many advanced image processing applications.
