臺灣博碩士論文加值系統

本?文針對可調性視訊編碼之空間可調性編碼(Spatial Scalable Coding)提出縮小取樣(Down Sampling)與放大取樣(Up Sampling)?波器。改?型之縮小取樣?波器採用雙向?波器特性及適應式?波器長?之方法，?波器可有效地減少邊緣資訊失真，可將影像同質區域平?化並保?非同質區域之細節部份。因此，其可減少基礎層(Base Layer)編碼位元。並且，由於保?邊緣之特性，使基礎層提供增強層(Enhancement Layer)較好的預測，因此亦可?低增強層的編碼位元。在影像中，本文以梯?運算方法，將邊緣與非邊緣作分?。在影像邊緣上缺失之像素，使用方向性內插法。實驗結果顯示，當提出的縮小取樣?波器在基礎層編碼?低約20%的位元?時，增強層可減少1.5%
的編碼位元。所提出的方向性內插方法，可提升PSNR 值約0.01dB~0.26dB，?低位元?約0.2%~16.3%。

This thesis proposes a downsampling filter and an upsampling filter for spatial scalable video coding. The bilateral filter and adaptive filter length concepts are used in downsampling filter to reduce the loss of edge information in images. By smoothing the homogeneous area and preserving the details in the non-homogeneous area of images, the coding bits are reduced in the base layer coding. At the same time, the edge-preserving property in the base layer also provides a better prediction to save the coding bits in the enhancement layer. For upsampling filter, the direction information of an image is used.
The local gradient determines the edges of an image. The missing pixels on the edges are obtained by performing the directional interpolation. Experimental results show that, for proposed downsampling filter, 1.5% bit-rate reduction is achieved in the enhancement layer while decreasing about 20% bit-rates on average in the base layers. For the roposed
directional upsampling filter, the PSNR improvement and bit-rate reduction are 0.01dB~0.26dB and 0.2%~16.3%, respectively.

Abstract ii
Acknowledgement iii
List of Tables vii
List of Figures viii
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Organization of the Thesis 2
Chapter 2 Spatial Scalability and Filters 4
2.1 Scalable Video Coding Architecture 4
2.1.1 Concepts of Scalability 6
2.2 Spatial Scalability 9
2.2.1 Interlayer Mechanisms in Spatial Scalability 11
2.2.2 Interlayer Motion Prediction 11
2.2.3 Interlayer Intra Texture Prediction 12
2.2.4 Interlayer Residual Prediction 13
2.3 Resampling Methods for Spatial Scalability 13
2.3.1 Downsampling Filter in the SVC 14
2.3.2 Upsampling Filters in the SVC 15
2.3.2.1 Summary of Upsampling Methods in SVC 19
2.3.3 Related Filter Designs 20
Chapter 3 Proposed Scaling Filters 22
3.1 Bilateral-based Downsampling Filter 22
3.1.1 Edge Detection 28
3.1.2 Bilateral Downsampling 29
3.2 Directional-based Upsampling Filter 32
3.2.1 Edge Detection 33
3.2.2 Directional Decision-making 33
3.2.3 Directional Interpolation 36
3.3 Summary 38
Chapter 4 Simulation Results and Comparisons 39
4.1 Experimental Environment Settings 39
4.2 Bilateral-based Downsampling Filter 40
4.3 Directional-based Upsampling Filter 49
Chapter 5 Conclusions and Future Work 53
5.1 Conclusions 53
5.2 Future Work 54
References 55

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