hardware implementation of data compression ... - INFN Bologna

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132 Wavelet based compression algorithm s a 5 d 5 d 4 d 3 −50 40 20 d 0 2 −20 −40 d 1 150 100 50 0 30 20 10 10 0 −10 20 0 −20 50 0 20 0 −20 Decomposition at level 5 : s = a5 + d5 + d4 + d3 + d2 + d1 . 1 2 3 4 5 6 Figure 5.1: Uni-dimensional analysis on 5 levels of the signal S – the coefficients Cth have been synthesized into the signal R, using the filters H and G. Both in the uni-dimensional and in the bi-dimensional case, the performances related to compression have been quantified using the percentage P of the number of null coefficients in Cth, while the performances related to the reconstruction error have been quantified using the root mean square error E between the original signal S and the signal R, obtained after the analysis and synthesis of Cth. In particular, since the total number of elements in Cth is 65536, in the uni-dimensional case, the parameter P can be expressed in the following way: P = 100 · (number of null coefficients in Cth) 65536 x 10 4 (5.3) Even the total number of elements in S and in R is 65536, so, if si is the i-th element of the uni-dimensional signal S and ri is the i-th
5.2 — Multiresolution algorithm optimization 50 100 150 200 250 Original Image 50 100 150 200 250 Synthesized Image dwt idwt Approximation coef. at level 5 Image Selection Decomposition at level 5 Figure 5.2: Bi-dimensional analysis on 5 levels of the signal S element of R, the parameter E can be expressed in the following way: E = 1 65536 (si − ri) 65536 2 (5.4) In the bi-dimensional case P is calculated in the same way while, naming si,j as the (i, j)-th element of S and ri,j as the (i, j)-th element of R, the parameter E can be expressed in the following way: E = 1 256 256 (si,j − ri,j) 65536 2 (5.5) i=1 Even if the parameters P and E cannot be directly comparable to the results obtained in the compression algorithms implemented on the CARLOS prototypes, they give an important indication about the performance of each filter set used during the analysis. In particular, P gives a rough estimation of how much the coefficients Cth can be compressed using the run length encoding, while E can i=1 j=1 133
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UNIVERSITÀ DEGLI STUDI DI BOLOGNA
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Contents Introduction ix 1 The ALIC
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CONTENTS 4 2D compression algorithm
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Introduction This thesis work has b
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Chapter 1 The ALICE experiment ALIC
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1.1 — The Inner Tracking System 1
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1.1 — The Inner Tracking System t
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1.1 — The Inner Tracking System P
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1.2 — Design of the drift layers
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1.3 — The SDDs (Silicon Drift Det
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PASCAL AMBRA 1.4 — SDD readout sy
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data_in[0] data_in[1] data_in[2] da
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1.4 — SDD readout system 1.4.2 Ev
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1.4 — SDD readout system with a c
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Chapter 2 Data compression techniqu
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2.2 — Remarks on information theo
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2.3 — Compression techniques 2.3.
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2.4 — Lossless compression techni
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Original sequence Sequence after di
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2.5 — Lossy compression technique
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2.6 — Implementation of compressi
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Symlets sym2 sym3 sym4 sym8 Wavelet
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Chapter 3 1D compression algorithm
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3.2 — 1D compression algorithm Fi
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3.3 — 1D algorithm performances s
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3.3 — 1D algorithm performances F
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3.4 — CARLOS v1 Figure 3.6: CARLO
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3.4 — CARLOS v1 Figure 3.7: Pictu
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3.4 — CARLOS v1 3.4.3 Functions p
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3.5 — CARLOS v2 have a 100% compa
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3.5 — CARLOS v2 3.5.1 The firstch
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3.5 — CARLOS v2 data and when loa
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3.5 — CARLOS v2 which of the 8 qu
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- indat6 : input 32-bit bus; - inda
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3.5 — CARLOS v2 - femux is a mult
Page 93 and 94: 3.5 — CARLOS v2 total optical fib
Page 95 and 96: 3.5 — CARLOS v2 Figure 3.11: Desi
Page 97 and 98: 3.5 — CARLOS v2 that CARLOS will
Page 99 and 100: 3.6 — CARLOS v2 design flow Figur
Page 101 and 102: 3.7 — Tests performed on CARLOS v
Page 103 and 104: Chapter 4 2D compression algorithm
Page 105 and 106: 4.1 — 2D compression algorithm Fi
Page 111 and 112: 4.2 — CARLOS v3 vs. the previous
Page 113 and 114: 4.3 — The final readout architect
Page 115 and 116: 4.5 — CARLOS v3 building blocks -
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Page 119 and 120: 4.5 — CARLOS v3 building blocks F
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Page 125 and 126: 4.5 — CARLOS v3 building blocks o
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Page 131 and 132: 4.5 — CARLOS v3 building blocks a
Page 133 and 134: 4.5 — CARLOS v3 building blocks p
Page 135 and 136: 4.7 — CARLOS layout features post
Page 137 and 138: Chapter 5 Wavelet based compression
Page 139 and 140: levels used: 5.1 — Wavelet based
Page 141 and 142: 5.2 — Multiresolution algorithm o
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Page 153 and 154: 5.3 — Choice of the architecture
Page 155 and 156: 5.3 — Choice of the architecture
Page 157 and 158: Dettaglio 1 1 D1 2 Downsample Hi_De
Page 159 and 160: 2 Upsample Dettaglio 1 1 D1 Hi_Rec
Page 161 and 162: 5.4 — Multiresolution algorithm p
Page 163 and 164: 5.5 — Hardware implementation ter
Page 165 and 166: 5.5 — Hardware implementation Fig
Page 167 and 168: 5.5 — Hardware implementation com
Page 169 and 170: 5.5 — Hardware implementation Haa
Page 171 and 172: Conclusions The main goal of this t
Page 173 and 174: Bibliography [1] ALICE Collaboratio
Page 175: BIBLIOGRAPHY [19] D. Cavagnino, P.
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