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Tay-shen Wang - One of the best experts on this subject based on the ideXlab platform.

  • An efficient spatial prediction-based image Compression Scheme
    IEEE Transactions on Circuits and Systems for Video Technology, 2002
    Co-Authors: Tzu-chuan Chou, Tay-shen Wang
    Abstract:

    We have designed a spatial prediction-based image-Compression Scheme. The proposed Scheme consists of two phases: the prediction phase and the quantization phase. In the prediction phase, a hierarchical structure among pixels in the image is built. Following the constructed hierarchical structure, the neighboring pixels are utilized to predict every central pixel. The prediction Scheme generates an image map which indicates the prediction errors. The structure of the resulting image map is very similar to the result of a discrete wavelet transform. Thus, most quantization methods of wavelet or subband image-Compression algorithms can be followed in our Scheme directly to yield good Compression performance. In the quantization phase, we design a multilevel threshold Scheme to further enhance the result of SPIHT by taking the significance of the pixel values and the hierarchical levels into account. Furthermore, the proposed Scheme can be realized by only a few integer additions and bit shifts. Simulation results indicate that the visual quality of the designed efficient spatial prediction-based image Compression Scheme is competitive with JPEG. All the above features make the designed image-Compression Scheme beneficial to the applications of real-time and wireless transmission in low-computational power environments.

  • ISCAS - An efficient spatial prediction-based image Compression Scheme
    2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 1
    Co-Authors: Chin-hwa Kuo, Tzu-chuan Chou, Tay-shen Wang
    Abstract:

    An efficient spatial prediction-based progressive image Compression Scheme is developed in this paper. The proposed Scheme consists of two phases, namely, the prediction phase and the quantization phase. In the prediction phase, information of the nearest neighbor pixels is utilized to predict the center pixel. Next in-place processes are taken, i.e., the resulting prediction error is stored in the same memory location as the predicted pixel. Thus, the temporary storage space required is significantly reduced in the encoding process as well as decoding process. The prediction Scheme generates prediction error images with hierarchical structure, which can employ the result of many existing quantization Schemes, such as EZW and SPIHT algorithms. As a result, a progressive coding feature is obtained in a straightforward manner. In the quantization phase, we extend the multilevel threshold Scheme. Not only the pixel intensity value itself but also level significance is taken into account. In the experimental testing, we illustrate that the proposed Scheme yields Compression quality advantages. It outperforms several existing image Compression Schemes. Furthermore, the proposed Scheme can be realized by only integer addition and shift operations. Tremendous amounts of computation-saving are achieved. The above features make the proposed image Compression Scheme beneficial to the areas of real-time applications and wireless transmission in limited bandwidth and low computation power environments.

Lijuan Sun - One of the best experts on this subject based on the ideXlab platform.

  • a distributed image Compression Scheme for energy harvesting wireless multimedia sensor networks
    Sensors, 2020
    Co-Authors: Chong Han, Jian Zhou, Songtao Zhang, Biao Zhang, Lijuan Sun
    Abstract:

    As an emerging technology, edge computing will enable traditional sensor networks to be effective and motivate a series of new applications. Meanwhile, limited battery power directly affects the performance and survival time of sensor networks. As an extension application for traditional sensor networks, the energy consumption of Wireless Multimedia Sensor Networks (WMSNs) is more prominent. For the image Compression and transmission in WMSNs, consider using solar energy as the replenishment of node energy; a distributed image Compression Scheme based on solar energy harvesting is proposed. Two level clustering management is adopted. The camera node-normal node cluster enables camera nodes to gather and send collected raw images to the corresponding normal nodes for Compression, and the normal node cluster enables the normal nodes to send the compressed images to the corresponding cluster head node. The re-clustering and dynamic adjustment methods for normal nodes are proposed to adjust adaptively the operation mode in the working chain. Simulation results show that the proposed distributed image Compression Scheme can effectively balance the energy consumption of the network. Compared with the existing image transmission Schemes, the proposed Scheme can transmit more and higher quality images and ensure the survival of the network.

  • a distributed image Compression Scheme for energy harvesting wireless multimedia sensor networks
    Mobile Ad-hoc and Sensor Networks, 2019
    Co-Authors: Chong Han, Jian Zhou, Songtao Zhang, Biao Zhang, Lijuan Sun
    Abstract:

    A distributed image Compression Scheme based on solar energy harvesting is proposed to address the problem of image transmission in wireless multimedia sensor networks. Two-level clustering management is adopted. The camera node-normal node cluster enables camera nodes to gather and send collected raw images to the corresponding normal nodes for Compression, and the normal node cluster enables the normal nodes to send the compressed images to the corresponding cluster head node. The re-clustering and dynamic adjustment methods for normal nodes are proposed to adaptive adjustment the operation mode in the working chain. Simulation results show that the proposed distributed image Compression Scheme can effectively balance the energy consumption of the network. Compared with the existing image transmission Schemes, the proposed Scheme can transmit more and higher quality images and ensure the survival of the network.

Tzu-chuan Chou - One of the best experts on this subject based on the ideXlab platform.

  • An efficient spatial prediction-based image Compression Scheme
    IEEE Transactions on Circuits and Systems for Video Technology, 2002
    Co-Authors: Tzu-chuan Chou, Tay-shen Wang
    Abstract:

    We have designed a spatial prediction-based image-Compression Scheme. The proposed Scheme consists of two phases: the prediction phase and the quantization phase. In the prediction phase, a hierarchical structure among pixels in the image is built. Following the constructed hierarchical structure, the neighboring pixels are utilized to predict every central pixel. The prediction Scheme generates an image map which indicates the prediction errors. The structure of the resulting image map is very similar to the result of a discrete wavelet transform. Thus, most quantization methods of wavelet or subband image-Compression algorithms can be followed in our Scheme directly to yield good Compression performance. In the quantization phase, we design a multilevel threshold Scheme to further enhance the result of SPIHT by taking the significance of the pixel values and the hierarchical levels into account. Furthermore, the proposed Scheme can be realized by only a few integer additions and bit shifts. Simulation results indicate that the visual quality of the designed efficient spatial prediction-based image Compression Scheme is competitive with JPEG. All the above features make the designed image-Compression Scheme beneficial to the applications of real-time and wireless transmission in low-computational power environments.

  • ISCAS - An efficient spatial prediction-based image Compression Scheme
    2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 1
    Co-Authors: Chin-hwa Kuo, Tzu-chuan Chou, Tay-shen Wang
    Abstract:

    An efficient spatial prediction-based progressive image Compression Scheme is developed in this paper. The proposed Scheme consists of two phases, namely, the prediction phase and the quantization phase. In the prediction phase, information of the nearest neighbor pixels is utilized to predict the center pixel. Next in-place processes are taken, i.e., the resulting prediction error is stored in the same memory location as the predicted pixel. Thus, the temporary storage space required is significantly reduced in the encoding process as well as decoding process. The prediction Scheme generates prediction error images with hierarchical structure, which can employ the result of many existing quantization Schemes, such as EZW and SPIHT algorithms. As a result, a progressive coding feature is obtained in a straightforward manner. In the quantization phase, we extend the multilevel threshold Scheme. Not only the pixel intensity value itself but also level significance is taken into account. In the experimental testing, we illustrate that the proposed Scheme yields Compression quality advantages. It outperforms several existing image Compression Schemes. Furthermore, the proposed Scheme can be realized by only integer addition and shift operations. Tremendous amounts of computation-saving are achieved. The above features make the proposed image Compression Scheme beneficial to the areas of real-time applications and wireless transmission in limited bandwidth and low computation power environments.

N. Blanchot - One of the best experts on this subject based on the ideXlab platform.

  • Experimental demonstration of a synthetic aperture Compression Scheme for multi-Petawatt high-energy lasers
    Optics Express, 2010
    Co-Authors: N. Blanchot, E Bar, G. Behar, C Bellet, D. Bigourd, F Boubault, C. Chappuis, H. Coïc, C. Damiens-dupont, O Flour
    Abstract:

    We present the experimental demonstration of a subaperture Compression Scheme achieved in the PETAL (PETawatt Aquitaine Laser) facility. We evidence that by dividing the beam into small subapertures fitting the available grating size, the sub-beam can be individually compressed below 1 ps, synchronized below 50 fs and then coherently added thanks to a segmented mirror. " Split-aperture laser pulse compressor design tolerant to alignment and line-density differences,

  • Experimental demonstration of a synthetic aperture Compression Scheme for multi-Petawatt high-energy lasers
    Optics Express, 2010
    Co-Authors: Jérôme Néauport, N. Blanchot, E Bar, G. Behar, C Bellet, D. Bigourd, F Boubault, C. Chappuis, H. Coïc, C. Damiens-dupont
    Abstract:

    We present the experimental demonstration of a subaperture Compression Scheme achieved in the PETAL (PETawatt Aquitaine Laser) facility. We evidence that by dividing the beam into small subapertures fitting the available grating size, the sub-beam can be individually compressed below 1 ps, synchronized below 50 fs and then coherently added thanks to a segmented mirror.

  • Synthetic aperture Compression Scheme for a multipetawatt high-energy laser.
    Applied optics, 2006
    Co-Authors: N. Blanchot, G. Marre, Jérôme Néauport, E. Sibé, C. Rouyer, S. Montant, A. Cotel, C. Le Blanc, C. Sauteret
    Abstract:

    High-energy petawatt lasers using the chirped-pulse amplification technique require meter-sized gratings to limit the beam fluence on the surface of the grating. An alternative, studied by many groups, is a mosaic grating consisting of smaller, coherently added gratings. We propose what we believe to be a new Compression Scheme consisting of beam phasing instead of grating mosaic phasing. This synthetic aperture Compression Scheme allows us to control the beam thanks to a unique segmented mirror equipped with three degrees of freedom. With this configuration, the beam is divided into small subapertures adapted to the classical grating size. After Compression, these subapertures are coherently added before the focusing stage. Therefore the alignment processes are simplified.

Sarangapani Jagannathan - One of the best experts on this subject based on the ideXlab platform.

  • WCNC - A New Adaptive Compression Scheme for Data Aggregation in Wireless Sensor Networks
    2010 IEEE Wireless Communication and Networking Conference, 2010
    Co-Authors: Priya Kasirajan, Carl Larsen, Sarangapani Jagannathan
    Abstract:

    Wireless sensor nodes typically have limited processing capabilities and are powered by batteries. The amount of energy expended in transmitting a single data bit would be several orders of magnitude higher when compared to the energy needed for a 32 bit computation. Thus, to maximize network lifetime, data transmissions should be minimized without losing vital information. In this paper, a novel adaptive Compression Scheme using nonlinear estimation theory is proposed for data aggregation. Satisfactory performance of the proposed Compression Scheme in the presence of noise, distortion, and quantization errors is demonstrated using Lyapunov approach. The proposed Scheme is contrasted with existing Compression Schemes using various metrics applicable to wireless sensor networks such as energy efficiency, distortion and Compression ratio. Simulation and hardware experimental results demonstrate almost 50% energy savings with very low distortion (less than 5%) and overhead. By iteratively applying the proposed Scheme at the cluster head nodes, higher energy savings are obtained with a tolerable level of distortion.