2,198 research outputs found
An efficient error resilience scheme based on wyner-ziv coding for region-of-Interest protection of wavelet based video transmission
In this paper, we propose a bandwidth efficient error resilience scheme for wavelet based video
transmission over wireless channel by introducing an additional Wyner-Ziv (WZ) stream to protect region of
interest (ROI) in a frame. In the proposed architecture, the main video stream is compressed by a generic
wavelet domain coding structure and passed through the error prone channel without any protection.
Meanwhile, the predefined ROI area related wavelet coefficients obtained after an integer wavelet transform
will be specially protected by WZ codec in an additional channel during transmission. At the decoder side, the error-prone ROI related wavelet coefficients will be used as side information to help decoding the WZ stream. Different size of WZ bit streams can be applied in order to meet different bandwidth condition and different
requirement of end users. The simulation results clearly revealed that the proposed scheme has distinct advantages in saving bandwidth comparing with fully applied FEC algorithm to whole video stream and in the meantime offer the robust transmission over error prone channel for certain video applications
Reliable Linear, Sesquilinear and Bijective Operations On Integer Data Streams Via Numerical Entanglement
A new technique is proposed for fault-tolerant linear, sesquilinear and
bijective (LSB) operations on integer data streams (), such as:
scaling, additions/subtractions, inner or outer vector products, permutations
and convolutions. In the proposed method, the input integer data streams
are linearly superimposed to form numerically-entangled integer data
streams that are stored in-place of the original inputs. A series of LSB
operations can then be performed directly using these entangled data streams.
The results are extracted from the entangled output streams by additions
and arithmetic shifts. Any soft errors affecting any single disentangled output
stream are guaranteed to be detectable via a specific post-computation
reliability check. In addition, when utilizing a separate processor core for
each of the streams, the proposed approach can recover all outputs after
any single fail-stop failure. Importantly, unlike algorithm-based fault
tolerance (ABFT) methods, the number of operations required for the
entanglement, extraction and validation of the results is linearly related to
the number of the inputs and does not depend on the complexity of the performed
LSB operations. We have validated our proposal in an Intel processor (Haswell
architecture with AVX2 support) via fast Fourier transforms, circular
convolutions, and matrix multiplication operations. Our analysis and
experiments reveal that the proposed approach incurs between to
reduction in processing throughput for a wide variety of LSB operations. This
overhead is 5 to 1000 times smaller than that of the equivalent ABFT method
that uses a checksum stream. Thus, our proposal can be used in fault-generating
processor hardware or safety-critical applications, where high reliability is
required without the cost of ABFT or modular redundancy.Comment: to appear in IEEE Trans. on Signal Processing, 201
Regularity scalable image coding based on wavelet singularity detection
In this paper, we propose an adaptive algorithm for scalable wavelet image coding, which is based on the general feature, the regularity, of images. In pattern recognition or computer vision, regularity of images is estimated from the oriented wavelet coefficients and quantified by the Lipschitz exponents. To estimate the Lipschitz exponents, evaluating the interscale evolution of the wavelet transform modulus sum (WTMS) over the directional cone of influence was proven to be a better approach than tracing the wavelet transform modulus maxima (WTMM). This is because the irregular sampling nature of the WTMM complicates the reconstruction process. Moreover, examples were found to show that the WTMM representation cannot uniquely characterize a signal. It implies that the reconstruction of signal from its WTMM may not be consistently stable. Furthermore, the WTMM approach requires much more computational effort. Therefore, we use the WTMS approach to estimate the regularity of images from the separable wavelet transformed coefficients. Since we do not concern about the localization issue, we allow the decimation to occur when we evaluate the interscale evolution. After the regularity is estimated, this information is utilized in our proposed adaptive regularity scalable wavelet image coding algorithm. This algorithm can be simply embedded into any wavelet image coders, so it is compatible with the existing scalable coding techniques, such as the resolution scalable and signal-to-noise ratio (SNR) scalable coding techniques, without changing the bitstream format, but provides more scalable levels with higher peak signal-to-noise ratios (PSNRs) and lower bit rates. In comparison to the other feature-based wavelet scalable coding algorithms, the proposed algorithm outperforms them in terms of visual perception, computational complexity and coding efficienc
Medical Image Compression using Lifting based New Wavelet Transforms
In this paper, the construction of new lifting based wavelets by a new method of calculating lifting coefficients is presented. First of all, new basis functions are utilized to ease new orthogonal traditional wavelets. Then by using the decomposing poly-phase matrix the lifting steps are calculated using a simplified method. The interesting feature of lifting scheme is that the construction of wavelet is derived in spatial domain only; hence the difficulty in the design of traditional wavelets is avoided. Lifting scheme was used to generate second generation wavelets which are not necessarily translation and dilation of one particular function. Short and sharp basis functions are chosen so as to obtain the non-uniform nature of usual image classes. Implemented wavelets are applied on a number of medical images. It was found that the compression ratio (CR) and Peak Signal to Noise Ratio (PSNR) are far ahead of that are obtained with the popular traditional wavelets as well as the successful 5/3 and 9/7 lifting based wavelets. Set Partitioning in Hierarchical Trees (SPIHT) is used to incorporate compression.DOI:http://dx.doi.org/10.11591/ijece.v4i5.596
Contributions in image and video coding
Orientador: Max Henrique Machado CostaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A comunidade de codificação de imagens e vídeo vem também trabalhando em inovações que vão além das tradicionais técnicas de codificação de imagens e vídeo. Este trabalho é um conjunto de contribuições a vários tópicos que têm recebido crescente interesse de pesquisadores na comunidade, nominalmente, codificação escalável, codificação de baixa complexidade para dispositivos móveis, codificação de vídeo de múltiplas vistas e codificação adaptativa em tempo real. A primeira contribuição estuda o desempenho de três transformadas 3-D rápidas por blocos em um codificador de vídeo de baixa complexidade. O codificador recebeu o nome de Fast Embedded Video Codec (FEVC). Novos métodos de implementação e ordens de varredura são propostos para as transformadas. Os coeficiente 3-D são codificados por planos de bits pelos codificadores de entropia, produzindo um fluxo de bits (bitstream) de saída totalmente embutida. Todas as implementações são feitas usando arquitetura com aritmética inteira de 16 bits. Somente adições e deslocamentos de bits são necessários, o que reduz a complexidade computacional. Mesmo com essas restrições, um bom desempenho em termos de taxa de bits versus distorção pôde ser obtido e os tempos de codificação são significativamente menores (em torno de 160 vezes) quando comparados ao padrão H.264/AVC. A segunda contribuição é a otimização de uma recente abordagem proposta para codificação de vídeo de múltiplas vistas em aplicações de video-conferência e outras aplicações do tipo "unicast" similares. O cenário alvo nessa abordagem é fornecer vídeo com percepção real em 3-D e ponto de vista livre a boas taxas de compressão. Para atingir tal objetivo, pesos são atribuídos a cada vista e mapeados em parâmetros de quantização. Neste trabalho, o mapeamento ad-hoc anteriormente proposto entre pesos e parâmetros de quantização é mostrado ser quase-ótimo para uma fonte Gaussiana e um mapeamento ótimo é derivado para fonte típicas de vídeo. A terceira contribuição explora várias estratégias para varredura adaptativa dos coeficientes da transformada no padrão JPEG XR. A ordem de varredura original, global e adaptativa do JPEG XR é comparada com os métodos de varredura localizados e híbridos propostos neste trabalho. Essas novas ordens não requerem mudanças nem nos outros estágios de codificação e decodificação, nem na definição da bitstream A quarta e última contribuição propõe uma transformada por blocos dependente do sinal. As transformadas hierárquicas usualmente exploram a informação residual entre os níveis no estágio da codificação de entropia, mas não no estágio da transformada. A transformada proposta neste trabalho é uma técnica de compactação de energia que também explora as similaridades estruturais entre os níveis de resolução. A idéia central da técnica é incluir na transformada hierárquica um número de funções de base adaptativas derivadas da resolução menor do sinal. Um codificador de imagens completo foi desenvolvido para medir o desempenho da nova transformada e os resultados obtidos são discutidos neste trabalhoAbstract: The image and video coding community has often been working on new advances that go beyond traditional image and video architectures. This work is a set of contributions to various topics that have received increasing attention from researchers in the community, namely, scalable coding, low-complexity coding for portable devices, multiview video coding and run-time adaptive coding. The first contribution studies the performance of three fast block-based 3-D transforms in a low complexity video codec. The codec has received the name Fast Embedded Video Codec (FEVC). New implementation methods and scanning orders are proposed for the transforms. The 3-D coefficients are encoded bit-plane by bit-plane by entropy coders, producing a fully embedded output bitstream. All implementation is performed using 16-bit integer arithmetic. Only additions and bit shifts are necessary, thus lowering computational complexity. Even with these constraints, reasonable rate versus distortion performance can be achieved and the encoding time is significantly smaller (around 160 times) when compared to the H.264/AVC standard. The second contribution is the optimization of a recent approach proposed for multiview video coding in videoconferencing applications or other similar unicast-like applications. The target scenario in this approach is providing realistic 3-D video with free viewpoint video at good compression rates. To achieve such an objective, weights are computed for each view and mapped into quantization parameters. In this work, the previously proposed ad-hoc mapping between weights and quantization parameters is shown to be quasi-optimum for a Gaussian source and an optimum mapping is derived for a typical video source. The third contribution exploits several strategies for adaptive scanning of transform coefficients in the JPEG XR standard. The original global adaptive scanning order applied in JPEG XR is compared with the localized and hybrid scanning methods proposed in this work. These new orders do not require changes in either the other coding and decoding stages or in the bitstream definition. The fourth and last contribution proposes an hierarchical signal dependent block-based transform. Hierarchical transforms usually exploit the residual cross-level information at the entropy coding step, but not at the transform step. The transform proposed in this work is an energy compaction technique that can also exploit these cross-resolution-level structural similarities. The core idea of the technique is to include in the hierarchical transform a number of adaptive basis functions derived from the lower resolution of the signal. A full image codec is developed in order to measure the performance of the new transform and the obtained results are discussed in this workDoutoradoTelecomunicações e TelemáticaDoutor em Engenharia Elétric
Motion Scalability for Video Coding with Flexible Spatio-Temporal Decompositions
PhDThe research presented in this thesis aims to extend the scalability range of the
wavelet-based video coding systems in order to achieve fully scalable coding with a
wide range of available decoding points. Since the temporal redundancy regularly
comprises the main portion of the global video sequence redundancy, the techniques
that can be generally termed motion decorrelation techniques have a central role in
the overall compression performance. For this reason the scalable motion modelling
and coding are of utmost importance, and specifically, in this thesis possible
solutions are identified and analysed.
The main contributions of the presented research are grouped into two
interrelated and complementary topics. Firstly a flexible motion model with rateoptimised
estimation technique is introduced. The proposed motion model is based
on tree structures and allows high adaptability needed for layered motion coding. The
flexible structure for motion compensation allows for optimisation at different stages
of the adaptive spatio-temporal decomposition, which is crucial for scalable coding
that targets decoding on different resolutions. By utilising an adaptive choice of
wavelet filterbank, the model enables high compression based on efficient mode
selection. Secondly, solutions for scalable motion modelling and coding are
developed. These solutions are based on precision limiting of motion vectors and
creation of a layered motion structure that describes hierarchically coded motion.
The solution based on precision limiting relies on layered bit-plane coding of motion
vector values. The second solution builds on recently established techniques that
impose scalability on a motion structure. The new approach is based on two major
improvements: the evaluation of distortion in temporal Subbands and motion search
in temporal subbands that finds the optimal motion vectors for layered motion
structure.
Exhaustive tests on the rate-distortion performance in demanding scalable video
coding scenarios show benefits of application of both developed flexible motion
model and various solutions for scalable motion coding
Mathematical transforms and image compression: A review
It is well known that images, often used in a variety of computer and other scientific and engineering applications, are difficult to store and transmit due to their sizes. One possible solution to overcome this problem is to use an efficient digital image compression technique where an image is viewed as a matrix and then the operations are performed on the matrix. All the contemporary digital image compression systems use various mathematical transforms for compression. The compression performance is closely related to the performance by these mathematical transforms in terms of energy compaction and spatial frequency isolation by exploiting inter-pixel redundancies present in the image data. Through this paper, a comprehensive literature survey has been carried out and the pros and cons of various transform-based image compression models have also been discussed
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