In this study, the performances of JPEG (the most widely used lossy image compression standard until it was published in 1992), JPEG2000 (designed to provide superior image quality at low bit rates) and JPEG XR (aimed...
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In this study, the performances of JPEG (the most widely used lossy image compression standard until it was published in 1992), JPEG2000 (designed to provide superior image quality at low bit rates) and JPEG XR (aimed to reach the speed of JPEG and the quality of JPEG2000) are evaluated with an application developed in C# language which is able to use different codecs. The results show that recently developed JPEG standard (JPEG XR) is able to compress images with the same quality as JPEG2000, but not the same speed as JPEG.
Dynamic bit allocation directly impacts the overall coding performance in block transform (e.g., DCT, Hadamard, etc.) coding, subband coding, and wavelet coding. In very low bit rate coding (such as the evolving MPEG-...
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Dynamic bit allocation directly impacts the overall coding performance in block transform (e.g., DCT, Hadamard, etc.) coding, subband coding, and wavelet coding. In very low bit rate coding (such as the evolving MPEG-4 standard), additional factors impacting the bit allocation process need to be identified and properly exploited to achieve optimal coding performance. In the paper, a generalized optimum dynamic bit allocation algorithm is presented. The algorithm is based on the Shannon rate-distortion bound and a weighted distortion criterion using a Lagrange multiplier optimization technique. The results look promising for applications in real-time multimedia communications.< >
A lattice vector quantization encoding method is developed based on ℓ 1 -norm-based enumeration and bit-plane coding. The algorithm is implemented for the cubic lattice, can handle arbitrary vector dimension, and is s...
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A lattice vector quantization encoding method is developed based on ℓ 1 -norm-based enumeration and bit-plane coding. The algorithm is implemented for the cubic lattice, can handle arbitrary vector dimension, and is suitable for transform, subband, or wavelet coding applications. Moreover, the algorithm can possibly extend to other binary lattices.
This paper will presents a mathematical model of finding a relations between dissimilar speeches signals which are speaker independent taken from common set of samples of Chhattisgarhi language and dialects commonly s...
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This paper will presents a mathematical model of finding a relations between dissimilar speeches signals which are speaker independent taken from common set of samples of Chhattisgarhi language and dialects commonly spoken at different regions of *** objective of this paper is to detect similar and dissimilar patterns of different Chhattisgarhi dialects through wavelet analysis methods which are useful for complex speech signal analysis.
For the past two decades, the Discrete wavelet Transformation (DWT) has been successfully applied to many fields. For imageprocessingapplications, the DWT can produce non-redundant representations of an input image ...
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For the past two decades, the Discrete wavelet Transformation (DWT) has been successfully applied to many fields. For imageprocessingapplications, the DWT can produce non-redundant representations of an input image with greater performance than other wavelet methods. Further, the DWT provides a better spatial and spectral localization of image representation, capable of revealing smaller changes, trends, and breakdown points that classical methods often miss. However, the DWT has its own limitations and disadvantages such as lack of shift invariance. That is, if the input signal or image is shifted, then the wavelet coefficients will exacerbate that shift. The DWT also lacks the ability to represent directional cases. The Double Density Dual-Tree Discrete wavelet Transformation (D3TDWT) is a relatively new and enhanced version of the DWT with two scaling functions and four distinct wavelets designed in such a way that one pair of wavelets is offset with another pair so that the first pair lies in between the second. In this paper, we propose a D3TDWT polarimetry analysis method to analyze Long Wave Infrared (LWIR) polarimetry imagery to discriminate objects such as people and vehicles from background clutter. The D3TDWT method can be applied to a wide range of applications such as change detection, shape extraction, target recognition, and simultaneous tracking and identification.
State-of-the-art in digital coding/decoding includes discrete image transformation, quantization, and entropy coding. The key to efficient data compression is associated with image transformation/reconstruction proces...
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State-of-the-art in digital coding/decoding includes discrete image transformation, quantization, and entropy coding. The key to efficient data compression is associated with image transformation/reconstruction processes. In this paper, we present a different filters wavelet-based intra-frame video coding technique. The wavelet transformation is developed and optimized in order to enhance the visual quality especially at very low bit rate. The proposed coding technique reduces the bit rate while performing well regarding PSNR and visual quality. In comparison with the conventional coding methods, our proposed coding technique provides significant performance gains in objective and subjective quality.
Ubiquitous use of real-time video communication on the Internet requires adaptive applications that can provide different levels of quality depending on the amount of resources available. For video coding this means t...
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Ubiquitous use of real-time video communication on the Internet requires adaptive applications that can provide different levels of quality depending on the amount of resources available. For video coding this means that the algorithms must be designed to be scalable in terms of bandwidth, processing requirements and quality of the reconstructed signal. This paper presents a novel video compression and coding algorithm targeted at delay-sensitive applications in heterogeneous network and computing environments. The algorithm, based on the embedded zerotree wavelet algorithm for still image compression, generates a highly scalable layered bitstream that can be decoded at different qualities in terms of spatial resolution, frame rate and compression distortion. Furthermore, the algorithm is designed to require only a minimal coding delay, making it suitable for highly interactive applications like videoconferencing. The performance of the proposed algorithm is evaluated by comparison with a nonscalable codec and the penalty in compression efficiency that the scalability requirement imposes is analyzed. The codec is shown to produce a scalable bitstream ranging from about 10 kbps to 10 Mbps, while the computational complexity is kept at a level that makes software implementation on CPU-constrained equipment feasible.
VLSI architectures play a vital role in most real-time applications because of their optimal performance. In this work, a single MAC (Multiply-Accumulate) based pipelined architecture is proposed for faster computatio...
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Many signal and imageprocessingapplications will be more benefited if the transform gives good spectral and temporal resolution in arbitrary regions of the time-frequency plane that is provided by the discrete wavel...
Many signal and imageprocessingapplications will be more benefited if the transform gives good spectral and temporal resolution in arbitrary regions of the time-frequency plane that is provided by the discrete wavelet packet transform (DWPT). In this paper, the architecture for lifting scheme based Daubechies 9/7 wavelet is proposed. The proposed architecture performs both forward and inverse transform. The architecture does not require any extra memory/FIFOs to store the intermediate results. The proposed architecture is verified by performing DWPT for images of size 64times64. The architecture has been described in VHDL at the RTL level and simulated successfully using ModelSim simulation environment
The Discrete wavelet Transform (DWT) is a signalprocessing technique popularised by its results in data compression. Considerable work has been done in designing novel architectures to perform the DWT, including a sy...
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The Discrete wavelet Transform (DWT) is a signalprocessing technique popularised by its results in data compression. Considerable work has been done in designing novel architectures to perform the DWT, including a systolic architecture designed by the authors, but little attention has been given to the inverse DWT which is needed in applications such as data compression for signal reconstruction. Despite the fact that the inverse DWT is computationally the reverse of the DWT, the hardware design for the architecture is not simply mirrored. Existing designs expect the architecture for the inverse DWT to be a simple follow-on step from the DWT design, however this is not the case. We present one such problem here, showing the FIFO buffering required on the input of the inverse architecture. We show how the size of this buffer can be calculated and compare it to a fixed data array implementation. This work is based on our systolic array design and is an integral part of the inverse DWT design we are working on for image and video compression.
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