本篇論文藉由之前的研究整合錯誤更正碼和影像修復技術的影像傳輸系統,提升系統抵抗干擾的能力。並在影像傳輸系統中加入遞迴式解碼技術,改善系統的效能。整合遞迴式解碼的錯誤更正碼主要架構是將解碼前和影像處理完的碼字做比較,利用其差值來判斷是否為擦失掉的依據,擦失完成後將剩餘的碼字送回解碼器做errors-and-erasures decoding。 近年來,因為低密度奇偶校驗碼可以依據系統特性調整碼字的長度以及具有較佳的錯誤更正能力使其變為熱門的研究項目。所以我們以前人的系統為基礎,提出一個影像傳輸系統,利用低密度奇偶校驗碼取代里德-所羅門碼,並依據低密度奇偶校驗碼加上五種不同影像修復的結果去做比較。此外,也利用結合通道的資訊和影像修復完的資訊提出一個遞迴解碼的架構。透過模擬結果將計算影像的Peak signal to noise ratio (PSNR) 值來比較系統抗干擾的能力。
This paper integrates error correction code and image restoration technology image transmission system by previous research to enhance the system's ability to resist interference. And in the image transmission system by adding recursive decoding technology to improve the system's performance. The main structure is to convert the decoding before and after the image processing code word comparison, the use of its difference to determine whether the basis for the wipe, wipe the completion of the remaining codeword back to the decoding Error-and-erasures decoding. In recent years, since the low density parity check code can adjust the length of the codeword according to the system characteristics and have a better error correction capability to make it a popular research project. So we based on the previous system, proposed a video transmission system, the use of low-density parity-check code to replace the Reed-Solomon code, and based on low-density parity-check code plus five different image restoration results to do more , Also use the information combined with the channel and image repair information submitted to a recursive decoding architecture. Through the simulation results, the peak signal to noise ratio (PSNR) of the image is calculated to compare the system's ability to resist interference.
為了持續優化網站功能與使用者體驗,本網站將Cookies分析技術用於網站營運、分析和個人化服務之目的。
若您繼續瀏覽本網站,即表示您同意本網站使用Cookies。