English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 56820/90522 (63%)
造訪人次 : 12249502      線上人數 : 55
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/117958

    題名: Error resilience for block compressed sensing with multiple-channel transmission
    作者: Huang, H.-C.;Chen, P.-L.;Chang, F.-C.
    關鍵詞: block compressed sensing;error resilience;reconstruction
    日期: 2019-12-24
    上傳時間: 2020-01-06 12:10:31 (UTC+8)
    摘要: Compressed sensing is well known for its superior compression performance, in existing schemes, in lossy compression. Conventional research aims to reach a larger compression ratio at the encoder, with acceptable quality reconstructed images at the decoder. This implies looking for compression performance with error-free transmission between the encoder and the decoder. Besides looking at compression performance, we applied block compressed sensing to digital images for robust transmission. For transmission over lossy channels, error propagation or data loss can be expected, and protection mechanisms for compressed sensing signals are required for guaranteed quality of the reconstructed images. We propose transmitting compressed sensing signals over multiple independent channels for robust transmission. By introducing correlations with multiple-description coding, which is an effective means for error resilient coding, errors induced in the lossy channels can effectively be alleviated. Simulation results presented the applicability and superiority of performance, depicting the effectiveness of protection of compressed sensing signals.
    關聯: Applied Sciences 10(1), p.161
    DOI: 10.3390/app10010161
    顯示於類別:[資訊創新與科技學系] 期刊論文


    檔案 描述 大小格式瀏覽次數
    Error Resilience for Block Compressed Sensing with Multiple-Channel Transmission.pdf7421KbAdobe PDF0檢視/開啟



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋