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研究生:陳哲興
研究生(外文):Che-Shing Chen
論文名稱:以移動向量為基礎之視訊錯誤隱藏演算法
論文名稱(外文):Motion Vector Based Error Concealment Algorithms For Video Coding
指導教授:陳美娟陳美娟引用關係
指導教授(外文):Mei-Juan Chen
學位類別:碩士
校院名稱:國立東華大學
系所名稱:電機工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:105
中文關鍵詞:視訊傳輸視訊編碼錯誤隱藏
外文關鍵詞:Video CommunicationError ConcealmentVideo Coding
相關次數:
  • 被引用被引用:0
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  • 下載下載:18
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藉由視訊傳播及多媒體應用的快速發展,由網路傳輸視訊資料變的很頻繁。為了將大量的視訊資料經由有限的頻寬傳送,在網路通道傳輸期間必須將視訊資料壓縮。壓縮的視訊位元流(bitstream)容易遭受到通道錯誤的干擾,即使位元錯誤率很小,也可能會嚴重的降低重建影像的品質。為了克服錯誤產生的影響,有許多技術被發展出來保護位元流。其中有些是在編碼端加入防護碼,並可結合通道防護編碼以增加壓縮位元流的抗擾性。另外有些技術是側重於解碼端做錯誤隱藏,包括偵測錯誤產生的位置及利用空間域及時間域的關聯性來復原錯誤。在本論文中,我們著重在解碼端研究時間域錯誤隱藏演算法。
有許多演算法有效利用相鄰二張畫面的相關性做錯誤隱藏而被提出。其中有些是基於區塊比對(block-matching)的準則,這種方法是將遺失區塊利用在前一張畫面尋找最佳匹配區塊來取代。另外有些演算法是用來復原遺失的移動向量(motion vector),可以利用鄰近或前一張畫面的移動向量並可結合邊界比對(boundary matching)準則來估測移動向量。此外,MFI用差值法以像素(pixel)為單位而不是以區塊為單位來估測移動向量。
相似於MFI,我們提出以移動向量為基礎的錯誤隱藏演算法是以像素為單位,根據相鄰移動向量間的相關性來復原每個像素的移動向量。我們利用移動向量間的趨勢性(tendency)可以更準確的估測每個像素的移動向量。另外,不只利用移動向量間的相關性,我們還利用像素間的相關性來估測移動向量。根據相鄰像素間的相關性可以將錯誤區塊內的像素區分為不同部分,而這些部分中每個像素的移動向量可以經由相關的移動向量做線性差值(linear interpolation)運算得到。因此,被破壞的影像可以重建為人眼所更能接受的影像。
For the rapid development of visual communication and multimedia applications, the transmission of image and video data via networks becomes frequently. In order to transmit the large data of image and video into the limited bandwidth channel, the image and video data must be compressed during the transmission through the network channel. Compressed video bitstream is sensitive to channel errors that may degrade the reconstructed images severely even the bit error rate is small. For combating the impact of errors, several techniques have been developed to protect the bitstream. One approach is adding some protection codes at the encoder, or combining the forward error correction to enhance the robustness of the highly compressed bitstream. Another approach centers on error concealment at the decoder, which includes to detect error positions and to conceal them using the spatial or/and temporal correlation. In this thesis, we focus on the research of temporal error concealment at the decoder.
In order to utilize the correlation between adjacent frames effectively for error concealment, several algorithms have been developed. One is based on block-matching criterion. The lost block can be replaced by the best matched block in the reference frame. Another is the recovery of lost motion vector. The lost motion vector of the error block can be estimated by the neighboring or temporal reference motion vectors or/and combining the boundary matching method. In addition, instead of estimating a motion vector per block, MFI estimates the motion vector per pixel using the interpolation kernel.
Like MFI method, we propose motion vector based error concealment algorithms to recover the displacement per pixel according to the relation of neighboring motion vectors. The displacement per pixel can be estimated more accurately by using the tendency of motion vectors. Besides, we use not only the relation among motion vectors, but also pixels. The pixels of the error block are divided into different parts according to their consistency with neighboring blocks and the displacement at each pixel of these parts is interpolated by relative motion vectors. Therefore, the damaged images can be reconstructed more acceptable by human eyes.
Abstract 1
Chapter 1 Introduction 3
1.1 Video Coding System 5
1.2 Error Control for Video Coding 9
1.3 Organization of this Thesis 13
Chapter 2 Review of Temporal Error Concealment Algorithms 15
2.1 Motion Vector Recovery Methods 16
2.1.1 Motion-Compensated Prediction 16
2.1.2 Motion Vector Selection with Boundary Matching Criterion 18
2.1.3 Overlapped Motion Compensation for Error Concealment 19
2.1.4 Motion Vector Rational Interpolation for Error Concealment 21
2.2 Motion Field Interpolation for Error Concealment 23
2.3 Multiframe-Based Error Concealment 26
2.4 Forward-Backward Block-Matching Error Concealment Method 27
Chapter 3 Proposed Temporal Error Concealment Algorithms 29
3.1 Properties of the Algorithms 30
3.1.1 Overview of the Decoding Procedure 30
3.1.2 Features of the Algorithms 31
3.2 Proposed Motion Vector Based Error Concealment Algorithms 36
3.2.1 Rectangular Motion Vector Interpolation 36
3.2.2 Diamond Motion Vector Interpolation 42
3.3 Motion Vector Forecast Procedure 51
Chapter 4 Performance Evaluation 52
4.1 Error Detection 53
4.2 Experimental Results 55
4.2.1 Results for Set 1 55
4.2.2 Results for Set 2 61
Chapter 5 Conclusions 74
5.1 Discussions 75
5.2 Future Work 80
Bibliography 82
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