A major problem in evaluating picture quality in image compression systems is the extreme difficulty in describing the type and amount of degradation in reconstructed image. Because of the inherent drawbacks associate...
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A major problem in evaluating picture quality in image compression systems is the extreme difficulty in describing the type and amount of degradation in reconstructed image. Because of the inherent drawbacks associated with the subjective measures of picture quality, there has been a great deal of interest in developing an objective measure that can be used as a substitute. The aim of this paper is to examine a set of objective picture quality measures for application in still image compression systems and to highlight the correlation of these measures with subjective picture quality measures. Picture quality is measured using nine different objective picture quality measures and subjectively using mean opinion score (MOS) as a measure of perceived picture quality. The correlation between each objective measure and MOS is found. The effects of different image compression ratios are assessed and the best objective measures are proposed. Our results show that some objective measures correlate well with the perceived picture quality for a given compression algorithm but they are not reliable for an evaluation across different algorithms. So, we compared objective picture quality measures across different algorithms and we found measures, which serve well in all tested image compression systems.
Several improvements to the Bugajski-Russo N-gram algorithm are proposed. When applied to English text these result in an algorithm with comparable complexity and approximately 10 to 30% less rate than the commonly us...
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Several improvements to the Bugajski-Russo N-gram algorithm are proposed. When applied to English text these result in an algorithm with comparable complexity and approximately 10 to 30% less rate than the commonly used COMPRESS algorithm.
Data compression techniques, such as image compression and speech compression, are useful in communication applications. We propose a simple speech compression algorithm using sub-band division and polynomial mapping ...
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Data compression techniques, such as image compression and speech compression, are useful in communication applications. We propose a simple speech compression algorithm using sub-band division and polynomial mapping quantization made from the piecewise linear quantization function for a voice-mail system. The voice-mail is an audio equivalent of sending letters. The main differences are that computer networks deliver the mail instead of a postman, and that electronic recording is used instead of a postman. Although speech data are stored in a semiconductor memory device, its capacity and the available network capacity are limited. Therefore, it is necessary to compress the data as much as possible. However there are two conditions to be satisfied: one is that the reconstructed data must be understood correctly. The other is that we must identify the sender. Signals with a rate of 64 kbit/sec are compressed at a ratio of about 1/13 using the proposed sub-band division and polynomial mapping quantization.
Image compression is a technique, which reduces the size of an image without much loss of information. In this paper we have put forward a new method for image compression that includes techniques such as Shannon-Fano...
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Image compression is a technique, which reduces the size of an image without much loss of information. In this paper we have put forward a new method for image compression that includes techniques such as Shannon-Fano - Elias coding followed by Run Length Encoding (RLE). By using parameters like Peak Signal to Noise Ratio(PSNR), Mean Square Error (MSE) the efficiency of our proposed algorithm is evaluated by giving square matrix image (256×256) as input.
Performance comparison between image compression methods is an activity difficult to realise because of the few standard environments for validation. The objective of this paper is to present OPENPRESS as a single ope...
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Performance comparison between image compression methods is an activity difficult to realise because of the few standard environments for validation. The objective of this paper is to present OPENPRESS as a single open platform for validation allowing the integration of most of the current and future image compression methods, to facilitate their comparison and validation on a common and coherent set of reference images. Another goal of OPENPRESS is to ensure a broad distribution of these compression methods to the potential users. For that purpose, the proposed environment involves advanced computer science techniques like distributed computing, platform-independent software engineering, client/server decomposition, etc.
A new wavelet-based method for the compression of electrocardiogram (ECG) data is presented. The discrete wavelet transform (DWT) is applied to the digitized ECG signal. The DWT coefficients are firstly quantized with...
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A new wavelet-based method for the compression of electrocardiogram (ECG) data is presented. The discrete wavelet transform (DWT) is applied to the digitized ECG signal. The DWT coefficients are firstly quantized with a uniform scalar dead zone quantizer. Then the quantized coefficients are decomposed into four symbol streams: a binary significance symbol stream, a sign stream, a position of the most significant bit (PMSB) symbol stream and a residual bits stream. An adaptive arithmetic coder with different context models is employed for the entropy coding of these symbol streams. Experiments on several records from the MIT-BIH arrhythmia database showed that the proposed coding algorithm outperforms other well-known wavelet-based ECG compression algorithms.
Data compression in cache memory allows increasing the effective capacity, which improves the hit rate and only insignificantly affects power consumption and die area. In this paper, the results of the first research ...
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ISBN:
(纸本)9781728104331
Data compression in cache memory allows increasing the effective capacity, which improves the hit rate and only insignificantly affects power consumption and die area. In this paper, the results of the first research on cache compression in processors with Elbrus architecture are presented. Base+Delta (B+Δ) and Base-Delta-Immediate (BΔI) compression algorithms are selected for hardware implementation for their high efficiency and lower decompression latency compared to other algorithms. The modified versions of these algorithms, B+Δ* and BΔI*, which allow to reduce implementation complexity and further shorten the latency, are presented. Additionally, a new set of compression schemes for modified algorithms (labeled as BΔI*-HL algorithm) is proposed to account for width of the interfaces and internal data buses. The algorithms were implemented using Verilog HDL and evaluated on FPGA prototype of Elbrus-8C2 processor and SPEC CPU2000 benchmark suite. The results show that BΔI* demonstrates almost equal of greater compression ration as the original BÄI algorithm while has significantly lower implementation complexity. The algorithm BΔI*-HL is proposed as the most suitable for hardware implementation with average compressed lines share of 24.4% and mean compression ratio of 1.246.
A new cost-effective and "near-lossless" quality compression system for images containing both video and graphics is presented. The scheme can be used successfully in two distinct architectures: for professi...
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A new cost-effective and "near-lossless" quality compression system for images containing both video and graphics is presented. The scheme can be used successfully in two distinct architectures: for professional video distribution from content provider to broadcaster, and for local memory reduction in a consumer DTV receiver.
In this paper, lifting scheme is adopted for aerial image compression and modified CDF97 (MCDF97) wavelet is put forward as wavelet kernel. MCDF97 lifting algorithm improves defect that five lifting coefficients of CD...
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In this paper, lifting scheme is adopted for aerial image compression and modified CDF97 (MCDF97) wavelet is put forward as wavelet kernel. MCDF97 lifting algorithm improves defect that five lifting coefficients of CDF97 wavelet are all irrational numbers. The compression performance of MCDF97 wavelet is almost the same as that of the CDF97 wavelet, but the algorithm based on MCDF97 wavelet reduces operation memory, decreases complexity and accelerates the processing speed. After wavelet transform of aerial images, set partitioning in hierarchical trees (SPIHT) coding is adopted to quantize and code the wavelet coefficients. Experimental results indicate that this compression algorithm greatly improves compression efficiency of aerial images, and meets the requirement of aerial compression system for storage, operation time and hardware implement.
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