motion estimation and compensation for very low bitrate video coding

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14 Chapter 1. Digital Video Coding at Very-Low BitRate Finally, the state of the art of video coding is discussed and some new investigations in image analysis are introduced. 1.1 Digital Video Digital images or frames consist of luminance (i.e. the brightness) and chrominance (i.e. the colors) intensities of regularly sampled points (the picture elements 1 ). The sampling process is performed either on a natural scene (digital camera) or on an \analog" image (digital scanning). The spatial information (in the two-dimensional space) is characterized by the image resolution. Instead of characterizing this resolution in pel=cm or pel=inch, it is generally expressed as the product pels=line lines, which is a measure independent from the screen size. A (digital) video sequence is a succession of (digital) images whose characteristic is the temporal resolution in terms of frames=s or images=s. This temporal domain information (the changes of image intensity along the time axis) is speci c to video transmission and raises the problems addressed in the present thesis, namely motion estimation and compensation. In its Recommendation 601 [12], the ITU-R (International Telecommunication Union - Radiocommunication, formerly CCIR) has de ned a way to digitize images in standard format (720 576). An extension of this de nition provides one with the di erent resolutions which should be used according to the target application (table 1.1), which directly introduces the required bitrate if no compression is achieved. Application Luminance Chrom. Aspect Temporal Bitrate resolution resolution ratio (fr:=s) (Mbit=s) HDTV 1920 1152 960 576 16=9 50 1800 TV (broad.) 720 576 360 576 4=3 25 166 TV (CD rec.) 360 288 180 144 4=3 25 31 Video phone 360 288 180 144 4=3 10 12:4 Mobile video 180 144 90 72 4=3 5 1:6 Table 1.1: CCIR 601 formats for moving pictures applications A few remarks can be made concerning table 1.1. At rst, the spatial resolution of the chrominance components is lower than the luminance one. 1 Commonly abbreviated as \pixels" or\pels".
1.2 Video Coding 15 These di erences result from the less important impact of colors on the Human Visual System (HVS). Secondly, achange of aspect ratio 2 (16=9 like for movies) accompanies the High De nition TV (HDTV) resolution. Another comment deals with the range of values of the luminance and chrominance components: digital images refer to components described by a nite number of bits, namely 8 bits for every luminance or chrominance pel. This 8-bit range allows values to go from 0 (black) to 255 (white) 3 . All these characteristics help computing the required bandwidths: table 1.1 introduces the necessary bitrates in Mbit=s. If one expects to transmit video telephony across an ISDN network (64kbit=s), one must rst nd a way to compress the signal by a factor superior to 194, while for mobile video transmission a compression ratio of only 25 is needed for ISDN networks. This factor rises again to 160 for mobile channels at 10kbit=s. Appendix A introduces some typical very-low bitrate sequences used to test the video compression algorithms. 1.2 Video Coding 1.2.1 Image Compression Compression is thus needed and is possible thanks to the reduction of the high redundancies and to the irrelevancies present in the data of a video sequence. The redundancy has to deal with the correlation and the predictability inherent to the pictures. Its use for compression purposes does not involve any loss of information. The irrelevancy exploits the perceptual limits of the HVS so as to avoid the transmission of invisible information. It introduces irreversible degradations. On a practical point of view, compression involves a succession of many di erent steps which aim at detecting what is redundant or irrelevant and how to encode it di erently. The following description proposes a 2 The aspect ratio is the ratio between the image width and height. 3 Generally, a color image may be described by a combination of three chromatic stimuli. Color television for instance uses the Red, Green and Blue (RGB) primary colors. Another possibility, usually used for video compression, is the Y luminance, plus two di erence chrominance signals: Cb and Cr,atlower spatial resolution like in table 1.1. People interested in more advanced readings concerning color treatment may consult [106].
Page 1: LABORATOIRE DE TELECOMMUNICATIONS E
Page 5: Avant-propos Mener a bien une these
Page 8 and 9: Resume L'estimation du mouvement re
Page 10 and 11: x 2.1.1 Apparent versus Real Motion
Page 12 and 13: xii A VLBR-like video sequences 167
Page 14 and 15: 2 Introduction Ancient Greece initi
Page 16 and 17: 4 Introduction Meanwhile, the desir
Page 18 and 19: 6 Introduction However, one can que
Page 20 and 21: 8 Introduction compensation in a vi
Page 22 and 23: 10 Introduction Once the proposed s
Page 25: Chapter 1 Digital Video Coding at V
Page 29 and 30: 1.2 Video Coding 17 { The redundanc
Page 31 and 32: 1.2 Video Coding 19 exhaustive use
Page 33 and 34: 1.4 Some (Very-) Low BitRate Codecs
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64 Chapter 2. Motion in the Framewo
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Chapter 4 Image Pre-Processing for
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4.1 Intuitive Rationale 97 (a) (b)
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4.1 Intuitive Rationale 99 (a) (b)
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4.2 Rate Distortion Conditions 101
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4.3 Experimental Results 107 Pre-pr
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4.3 Experimental Results 109 Mean P
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4.3 Experimental Results 111 From t
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4.3 Experimental Results 113 Origin
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4.4 Conclusion 119 4.4 Conclusion T
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122 Chapter 5. Mesh-Based Motion Co
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162 Conclusion so as to adapt the s
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164 Conclusion gain is not as obvio
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Appendix A VLBR-like video sequence
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VLBR-like video sequences 169 Coast
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Appendix B Rate Distortion theory A
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B.1 Information Theory 173 B.1 Info
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B.2 Discrete Memoryless Sources and
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B.3 Rate Distortion Function 177 B.
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B.4 Extension to Moving Pictures 17
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B.4 Extension to Moving Pictures 18
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184 Chapter C. Markov Random Fields
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186 Chapter C. Markov Random Fields
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Appendix D Complements to Chapter 5
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D.2 Pseudo-code of the implementati
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Bibliography [1] COST 211ter Simula
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Bibliography 205 [21] E. Decenciere
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Bibliography 207 [41] R.M. Gray. Ve
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Bibliography 209 [65] B. Macq, M.P.
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Bibliography 211 [86] H.G. Musmann,
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Bibliography 213 [110] M.P. Queluz
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Bibliography 215 [132] F. Vermaut,
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