The Experts below are selected from a list of 10281 Experts worldwide ranked by ideXlab platform

Chin-chen Chang - One of the best experts on this subject based on the ideXlab platform.

  • a new lossless compression scheme based on huffman Coding scheme for image compression
    Signal Processing-image Communication, 2000
    Co-Authors: Chin-chen Chang
    Abstract:

    Abstract A novel lossless image-compression scheme is proposed in this paper. A two-stage structure is embedded in this scheme. A linear predictor is used to decorrelate the raw image data in the first stage. Then in the second stage, an effective scheme based on the Huffman Coding method is developed to encode the residual image. This newly proposed scheme could reduce the cost for the Huffman Coding Table while achieving high compression ratio. With this algorithm, a compression ratio higher than that of the Lossless JPEG method for 512×512 images can be obtained. In other words, the newly proposed algorithm provides a good means for lossless image compression.

Yi Shen - One of the best experts on this subject based on the ideXlab platform.

  • A Medical Image Compression Scheme Based on Low Order Linear Predictor and Most-likely Magnitude Huffman Code
    2006 International Conference on Mechatronics and Automation, 2006
    Co-Authors: Xiaofeng Li, Yi Shen
    Abstract:

    In this paper, a fast lossless compression scheme is presented for the medical image. This scheme consists of two stages. In the first stage, a set of least-square-based linear prediction coefficients of each block are used to form the prediction of the current pixel. Predicted value of each pixel is subtracted from the actual value of the current pixel to form the residual image. In the second stage, an effective scheme based on the Huffman Coding method is developed to encode the residual image. This newly proposed scheme could reduce the cost for the Huffman Coding Table while achieving high compression ratio. With this algorithm, a compression ratio higher than that of the lossless JPEG, JPEG-LS and JPEG2000 method for image can be obtained. At the same time, this method is quickest of the three compression schemes. In other words, the newly proposed algorithm provides good means for lossless medical image compression

Xiaofeng Li - One of the best experts on this subject based on the ideXlab platform.

  • A Medical Image Compression Scheme Based on Low Order Linear Predictor and Most-likely Magnitude Huffman Code
    2006 International Conference on Mechatronics and Automation, 2006
    Co-Authors: Xiaofeng Li, Yi Shen
    Abstract:

    In this paper, a fast lossless compression scheme is presented for the medical image. This scheme consists of two stages. In the first stage, a set of least-square-based linear prediction coefficients of each block are used to form the prediction of the current pixel. Predicted value of each pixel is subtracted from the actual value of the current pixel to form the residual image. In the second stage, an effective scheme based on the Huffman Coding method is developed to encode the residual image. This newly proposed scheme could reduce the cost for the Huffman Coding Table while achieving high compression ratio. With this algorithm, a compression ratio higher than that of the lossless JPEG, JPEG-LS and JPEG2000 method for image can be obtained. At the same time, this method is quickest of the three compression schemes. In other words, the newly proposed algorithm provides good means for lossless medical image compression

Wayne Wolf - One of the best experts on this subject based on the ideXlab platform.

  • code compression for vliw embedded systems using a self generating Table
    IEEE Transactions on Very Large Scale Integration Systems, 2007
    Co-Authors: Chang Hong Lin, Yuan Xie, Wayne Wolf
    Abstract:

    We propose a new class of methods for VLIW code compression using variable-sized branch blocks with self-generating Tables. Code compression traditionally works on fixed-sized blocks with its efficiency limited by their small size. A branch block, a series of instructions between two consecutive possible branch targets, provides larger blocks for code compression. We compare three methods for compressing branch blocks: Table-based, Lempel-Ziv-Welch (LZW)-based and selective code compression. Our approaches are fully adaptive and generate the Coding Table on-the-fly during compression and decompression. When encountering a branch target, the Coding Table is cleared to ensure correctness. Decompression requires a simple Table lookup and updates the Coding Table when necessary. When deCoding sequentially, the Table-based method produces 4 bytes per iteration while the LZW-based methods provide 8 bytes peak and 1.82 bytes average decompression bandwidth. Compared to Huffman's 1 byte and variable-to-fixed (V2F)'s 13-bit peak performance, our methods have higher deCoding bandwidth and a comparable compression ratio. Parallel decompression could also be applied to our methods, which is more suiTable for VLIW architectures.

  • lzw based code compression for vliw embedded systems
    Design Automation and Test in Europe, 2004
    Co-Authors: Chang Hong Lin, Yuan Xie, Wayne Wolf
    Abstract:

    We propose a new variable-sized-block method for VLIW code compression. Code compression traditionally works on fixed-sized blocks and its ef.ciency is limited by the smallblock size. Branch blocks -- instructions between two consecutive possible branch targets -- provide larger blocks for code compression. We propose LZW-based algorithms to compress branch blocks. Our approach is fully adaptive and generates Coding Table on-the-fly during compression and decompression. When encountering a branch target,the Coding Table is cleared to ensure correctness. Decompression requires only a simple lookup and update when necessary. Our method provides 8 bytes peak decompression bandwidth and 1.82 bytes in average. Compared to Huffman's 1 byte and V2F's 13-bit peak performance, our methods have higher deCoding bandwidth and comparable compression ratio. Parallel decompression could also be applied to our methods, which is more suiTable for VLIW architecture.

Chang Hong Lin - One of the best experts on this subject based on the ideXlab platform.

  • code compression for vliw embedded systems using a self generating Table
    IEEE Transactions on Very Large Scale Integration Systems, 2007
    Co-Authors: Chang Hong Lin, Yuan Xie, Wayne Wolf
    Abstract:

    We propose a new class of methods for VLIW code compression using variable-sized branch blocks with self-generating Tables. Code compression traditionally works on fixed-sized blocks with its efficiency limited by their small size. A branch block, a series of instructions between two consecutive possible branch targets, provides larger blocks for code compression. We compare three methods for compressing branch blocks: Table-based, Lempel-Ziv-Welch (LZW)-based and selective code compression. Our approaches are fully adaptive and generate the Coding Table on-the-fly during compression and decompression. When encountering a branch target, the Coding Table is cleared to ensure correctness. Decompression requires a simple Table lookup and updates the Coding Table when necessary. When deCoding sequentially, the Table-based method produces 4 bytes per iteration while the LZW-based methods provide 8 bytes peak and 1.82 bytes average decompression bandwidth. Compared to Huffman's 1 byte and variable-to-fixed (V2F)'s 13-bit peak performance, our methods have higher deCoding bandwidth and a comparable compression ratio. Parallel decompression could also be applied to our methods, which is more suiTable for VLIW architectures.

  • lzw based code compression for vliw embedded systems
    Design Automation and Test in Europe, 2004
    Co-Authors: Chang Hong Lin, Yuan Xie, Wayne Wolf
    Abstract:

    We propose a new variable-sized-block method for VLIW code compression. Code compression traditionally works on fixed-sized blocks and its ef.ciency is limited by the smallblock size. Branch blocks -- instructions between two consecutive possible branch targets -- provide larger blocks for code compression. We propose LZW-based algorithms to compress branch blocks. Our approach is fully adaptive and generates Coding Table on-the-fly during compression and decompression. When encountering a branch target,the Coding Table is cleared to ensure correctness. Decompression requires only a simple lookup and update when necessary. Our method provides 8 bytes peak decompression bandwidth and 1.82 bytes in average. Compared to Huffman's 1 byte and V2F's 13-bit peak performance, our methods have higher deCoding bandwidth and comparable compression ratio. Parallel decompression could also be applied to our methods, which is more suiTable for VLIW architecture.