Although IBDI, a coding tool that increases internal bit depth to improve compression performance for high quality video, is able to significantly improve the coding efficiency, the internal memory increment problem o...
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Although IBDI, a coding tool that increases internal bit depth to improve compression performance for high quality video, is able to significantly improve the coding efficiency, the internal memory increment problem occurs because of the necessity of storing reference frames. Therefore, memory compression algorithm is proposed to solve the internal memory increment problem while maintaining the coding performance of IBDI. The memory compression methods have successively reduced the reference frame memory while preserving the coding efficiency by dividing a reference frame into the fixed size processing units and using additional information of each unit. However, additional information of each processing unit also has to be stored in internal frame memory; the amount of additional information could be a limitation of the effectiveness of memory compression scheme. Therefore, to relax this limitation of previous method, we propose a selective merging-based reference frame memory compression algorithm, dramatically reducing the amount of additional information. Simulation results show that the proposed algorithm provides much smaller overhead than that of the previous algorithm while keeping the coding efficiency of IBDI.
Nomadic computing often refers to people using computer support working anywhere, anytime and not necessarily attached to a specific location or time of the day. Mobile computing and wireless ad-hoc networks are impor...
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Nomadic computing often refers to people using computer support working anywhere, anytime and not necessarily attached to a specific location or time of the day. Mobile computing and wireless ad-hoc networks are important elements in this kind of scenarios. Nowadays it is common to see architects, engineers, geologists and/or designers working on the field and sharing ideas on a collaborative media using sketches and freehand writing. On this scenario, data overflow among the peer applications often happens, since the sketches have to be distributed among all participants in real time. This paper presents a work on characterization and compression algorithms for sketches, with and without loss of information, to be used on mobile devices, in order to reduce the data traffic. We focused our study on three parameters of the algorithms: time required characterizing and compressing the sketch, size of the resulting information and human perceived of lost information. Our results present algorithms with a compression ratio lower than 1% the size of the original image without information loosing under human perception.
We propose an algorithm for the compression of ECG signals, in particular QRS complexes, based on the expansion of signals with compact support into a basis of discrete Hermite functions. These functions are obtained ...
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We propose an algorithm for the compression of ECG signals, in particular QRS complexes, based on the expansion of signals with compact support into a basis of discrete Hermite functions. These functions are obtained by sampling continuous Hermite functions, previously used for the compression of ECG signals. Our algorithm uses the theory of signal models based on orthogonal polynomials, and achieves higher compression ratios compared with previously reported algorithms, both those using Hermite functions, as well as those using the discrete Fourier and discrete cosine transforms.
3D meshes are one of the most common representations of 3D objects that have been used in graphics applications. They often require a huge amount of data for storage and/or transmission. In this paper, we present a ne...
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3D meshes are one of the most common representations of 3D objects that have been used in graphics applications. They often require a huge amount of data for storage and/or transmission. In this paper, we present a new compression algorithm based on stripification of the geometric models that enables us to progressively visualize the 3D models during their transmission. The proposed algorithm encodes the geometry and the connectivity of the input model in an interwoven fashion. The main idea is to store 3D objects as strips files. The algorithm achieves compression ratios above 61 : 1 over ASCII encoded formats resulting in faster transmission and rendering of complex graphical objects.
In this work, we have implemented DCT data compression and a run-length approach to compress an ECG data signal and send the compressed data via a Bluetooth device to a mobile phone on which a .Net platform applicatio...
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In this work, we have implemented DCT data compression and a run-length approach to compress an ECG data signal and send the compressed data via a Bluetooth device to a mobile phone on which a .Net platform application has been installed. After reception of the compressed data, the original signal will be retrieved by the inverse DCT algorithm using the built-in application. The results have shown good compression performance indices. Transmission time is reduced due to the necessity of the energy conservation of the mobile battery and online application of telecardiology.
In this article, two algorithms are described that are suited for real-time biomedical signal compression. These being, Amplitude Threshold compression and SQ segment compression. Comparison of these methods with well...
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In this article, two algorithms are described that are suited for real-time biomedical signal compression. These being, Amplitude Threshold compression and SQ segment compression. Comparison of these methods with well known methods such as lossy Discrete Cosine Transform (DCT) and lossless Turning Point (TP) is shown. The compression method outputs were reconstructed using a cubic spline approximation and compared. The values of compression ratio (CR), percent mean square difference (PRD) and area criteria were chosen for method comparison. Here it is shown that the method presented here (Threshold, SQ segment) provide considerably lower CR values than the DCT method and slightly higher CR values than the TP method. However, the PRD value for both proposed methods is lower than the PRD values of reference methods DCT and TP.
This paper presents an algorithm for compressing long traces generated using RTL or other fast simulation. The compressed traces can be used by power analysis tools to estimate power on the original traces. We show th...
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ISBN:
(纸本)9781457713989
This paper presents an algorithm for compressing long traces generated using RTL or other fast simulation. The compressed traces can be used by power analysis tools to estimate power on the original traces. We show that the length of the compressed trace is independent of the length of original trace and is a function of circuit size (precisely, its active part) for which the trace was generated. Our experiments show up to 578× compression ratio on several long RTL traces (up to 320,000 clock transitions) used for power analysis on three industrial blocks (4K, 114K and 202K gates). This leads to significant runtime improvement, especially when the traces are reused over multiple power analysis runs. The dynamic power estimated using compressed traces is within 5% of the power analysis on original traces.
Energy efficiency is critical in the design and deployment of wireless sensor networks. Data compression is a significant approach to reducing energy consumption of data gathering in multi-hop sensor networks. Existin...
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Energy efficiency is critical in the design and deployment of wireless sensor networks. Data compression is a significant approach to reducing energy consumption of data gathering in multi-hop sensor networks. Existing compression algorithms, however, only apply to either lossless or lossy compression, but not to both. This paper presents a unified algorithmic framework to both lossless and lossy data compression, thus effectively supporting the desirable flexibility of choosing either lossless or lossy compression in an on-demand fashion based on given applications. We analytically prove that the performance of the proposed framework for lossless compression is superior to or at least equivalent to that of traditional predictive coding schemes regardless of any entropy encoders used. We demonstrate the merits of our proposed framework in comparison with other recently proposed compression algorithms for wireless sensor networks including LEC, S-LZW and LTC using various real-world sensor data sets.
The ECGs transmission problem becomes actual nowadays due to the tremendous progress in communications. One of the major aspects of the transmission is the source coding (compression). The wavelet theory becomes a too...
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The ECGs transmission problem becomes actual nowadays due to the tremendous progress in communications. One of the major aspects of the transmission is the source coding (compression). The wavelet theory becomes a tool frequently used in compression. The aim of this paper is a very fast compression algorithm based on wavelets. Some simulation results prove the performance of the proposed algorithm.
In this paper, a low power baseline JPEG image compressor architecture, to be interfaced directly with an image sensor, has been presented. It compresses the raster YCbCr 4:2:2 image data from the image sensor into JP...
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In this paper, a low power baseline JPEG image compressor architecture, to be interfaced directly with an image sensor, has been presented. It compresses the raster YCbCr 4:2:2 image data from the image sensor into JPEG format. The compressed image data are being packed into byte format and DMA can be used to retrieve the JPEG image. The JPEG image compression chip is designed using 0.18-μm CMOS technology. It consumes 1.69mW when compressing at 7.49 (VGA) frames per second.
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