Satellite data compression

2 Projection Pursuit-Based Component Analysis for Dimensionality Reduction......Page 3
 3 Projection Index-Based Prioritized PP......Page 5
 4 Initialization-Driven PIPP......Page 7
Cover......Page 1
 1 Introduction......Page 2
 Contents......Page 6
 Contributors......Page 8
  4.2 Enhancing Discriminant Informative Spectral Bands......Page 9
 1 Review of RandD of Satellite Data Compression at the Canadian Space Agency......Page 11
  1.3 Vector Quantization Data Compression......Page 12
  5.2 PI-PRPP......Page 15
  2.1 Successive Approximation Multi-Stage Vector Quantization (SAMVQ)......Page 16
 3 Evaluation of Near Lossless Features of SAMVQ and HSOCVQ......Page 18
 5 Impact of Pre-Processing and Radiometric Conversion on Compression Performance......Page 21
 6 Effect of Keystone and Smile on Compression Performance......Page 22
 7 Multi-Disciplinary User Acceptability Study for Compressed Data......Page 25
Satellite Data Compression......Page 4
  5.1 PIPP with Random Initial Conditions......Page 10
  4.4 Unsupervised Linear Unmixing......Page 13
 5 Conclusions......Page 14
  2.2 Hierarchical Self-Organizing Cluster Vector Quantization (HSOCVQ)......Page 17
 4 Effect of Anomalies on Compression Performance......Page 19
   6.2.2Logarithmic Quantization......Page 20
   8.1.11997 AVIRIS Data Set......Page 24
 8 Enhancement of Resilience to Bit-Errors of the Compression Techniques......Page 26
 References......Page 23
  8.3Discrimination of Materials......Page 30
 10 Participation in Development of International Standards for Satellite Data Systems......Page 31
 References......Page 27
 9 Development of On-Board Prototype Compressors......Page 28
 11 Summary......Page 32
 References......Page 35
 1 Introduction......Page 39
  2.1 First Compressors......Page 41
  2.2 DCT-Based Compressor......Page 42
  2.3 Wavelet-Based Compressor......Page 43
  2.4 A Standard for Space Applications: CCSDS Recommendation......Page 44
  3.1 Multispectral Compression......Page 45
  3.2 Wavelet Limitations......Page 46
  3.3 A New Transform for On-Board Compression......Page 47
  3.4 COTS for On-Board Compression......Page 48
  3.6 Selective Compression......Page 50
   3.6.1 On-Board Cloud-Detection Feasibility......Page 51
   3.6.2 ROI Coding......Page 52
  3.7 Fixed Quality: Variable Data Rate Compression......Page 53
 4 Conclusions......Page 54
 References......Page 55
Chapter 3: Low-Complexity Approaches for Lossless and Near-Lossless Hyperspectral Image Compression......Page 57
 1 Introduction and Motivation......Page 58
  2.1 Compression Techniques......Page 59
   2.2.1 CCSDS 101: Lossless Data Compression......Page 60
  2.2.3 JPEG-LS......Page 61
  4.1 Prediction......Page 63
   4.3.1 Golomb Coding......Page 65
   4.3.3 Coding of Predictor Parameters......Page 66
  4.5 Complexity......Page 67
  5.1 Dataset Description......Page 68
  5.3 AIRS......Page 69
  5.4 Near-Lossless Compression......Page 70
 6 Hardware Implementation......Page 71
 7 Conclusions......Page 73
 References......Page 74
 1 Introduction......Page 76
  2.1 Progressive Image Transmission......Page 78
  2.2 Set Partitioning Sorting Algorithm......Page 79
  2.3 Coding Algorithm......Page 80
 3 Listless SPIHT and FPGA Implementation......Page 81
  3.1 LZC......Page 82
  3.2 Proposed Listless SPIHT......Page 83
  3.3 Performance Analysis......Page 85
  3.4 FPGA Implementation......Page 87
   3.4.1 Line-based Wavelet Transform Structure......Page 88
   3.4.2 Bit-Plane Parallel VLSI Architecture for the L-SPIHT......Page 89
   3.4.3 Hardware Implementation......Page 90
 References......Page 93
Chapter 5: Outlier-Resilient Entropy Coding......Page 95
 1 Introduction and Motivation......Page 96
 2 Limitations of Rice and of CCSDS 121.0......Page 97
 3 Outlier-Resilient Codes......Page 98
  3.1 Subexponential Codes......Page 99
  3.2 Limited-Length Signed Rice Codes......Page 100
  3.3 Prediction Error Coder (PEC)......Page 101
  4.1 Modeling the Input Data......Page 104
  4.2 Performance Metrics......Page 106
  4.4 Subexponential Codes......Page 107
  4.5 Limited-Length Signed Rice Codes......Page 108
  4.6 PEC Codes......Page 109
  5.1 Adaptive Subexponential......Page 110
  5.3 Fully Adaptive PEC (FAPEC)......Page 111
  6.1 Synthetic Tests......Page 113
  6.2 Data Compression Corpus......Page 114
 7 Summary and Conclusions......Page 118
 References......Page 120
 1Introduction......Page 122
 2Lossless/Near-Lossless Image Compression Algorithms......Page 123
  2.1Prediction-Based DPCM......Page 124
  2.2Context Modeling for Entropy Coding......Page 125
 3Hyperspectral Data Compression Through DPCM......Page 126
 4Crisp/Fuzzy Classified 3D/Spectral Prediction......Page 127
  4.2Initialization......Page 128
   4.3.1S-FMP Membership Function and Training of Predictors......Page 130
   4.3.3Prediction......Page 132
  4.4Context Based Arithmetic Coding......Page 133
 5Lossless Hyperspectral Image Compression Based on LUTs......Page 134
   6.1.1Radiometric Distortion......Page 137
   6.1.2Spectral Distortion......Page 139
  6.2Linear and Logarithmic Quantization......Page 140
   6.2.1Linear Quantization......Page 141
 7Virtually Lossless Compression......Page 142
  8.1Lossless Compression Performance Comparisons......Page 144
   8.1.11997 AVIRIS Data Set......Page 145
   8.1.22006 AVIRIS Data Set......Page 146
  8.2Near Lossless Compression Performance Comparisons......Page 147
  8.3Discrimination of Materials......Page 151
 References......Page 152
 1 Introduction......Page 155
 2 Data......Page 156
 3 The Compression Scheme......Page 159
 4 Results......Page 165
 5 Conclusions......Page 173
 1 Introduction......Page 175
 2 Lossless Compression of Hyperspectral Images......Page 176
 4 Predictor Guided LUT Method......Page 178
 5 Uniform Quantization of Co-Located Pixels......Page 181
 6 Multiband LUT......Page 182
 7 Experimental Results......Page 183
 References......Page 188
 1 Introduction......Page 191
  2.1 Lifting Scheme and Applications......Page 194
  2.2 Reversible Integer Transform based on Multi-lifting Scheme......Page 195
  3.1 Matrix Factorization and Multi-lifting......Page 197
  3.2 Design of Reversible Integer to Integer TDLT/RKLT......Page 202
 4 Experimental Results and Discussion of RTDLT/RKLT-based Hyperspectral Image Compression......Page 207
 5 3D-RLT-based Hyperspectral Image Compression......Page 212
 6 Experimental Results of 3D-RLT-based Hyperspectral Image Compression......Page 213
 7 Conclusions......Page 216
 References......Page 217
 1 Introduction......Page 220
  2.1 Centering and Covariance Particularities......Page 222
  2.2 Spatial Subdivision......Page 223
  2.3 The Reversible KLT......Page 224
  3.1 Plain Clustering......Page 226
  3.2 Recursive Structure......Page 227
  3.3 Two-Level Structures......Page 228
  3.4 Multilevel Structures......Page 229
 4 Experimental Results......Page 231
 5 Summary......Page 235
 References......Page 236
 1 Introduction......Page 238
 2 Segmented Principal Component Analysis......Page 242
 3 SPCA+JPEG2000......Page 243
 4 Data Analysis Performance of SPCA+JPEG2000......Page 247
  4.1 Spectral Fidelity......Page 248
  4.4 Unsupervised Linear Unmixing......Page 250
 5 Sensor-Specific Suboptimal Partitions for SPCA+JPEG2000......Page 252
 6 Conclusion......Page 255
 1 Introduction......Page 257
 2 Data......Page 258
 3 Compression Scheme......Page 259
 4 Results......Page 264
 5 Summary......Page 266
 References......Page 270
 1 Introduction......Page 272
 2 Compression and Classification Accuracy......Page 273
 3 Feature Extraction and Compression......Page 276
  4.1 Pre-enhancing Discriminant Features......Page 277
  4.2 Enhancing Discriminant Informative Spectral Bands......Page 280
 5 Conclusions......Page 285
 References......Page 286
Chapter 14: Projection Pursuit-Based Dimensionality Reduction for Hyperspectral Analysis......Page 289
 1 Introduction......Page 290
 2 Projection Pursuit-Based Component Analysis for Dimensionality Reduction......Page 291
 3 Projection Index-Based Prioritized PP......Page 293
 4 Initialization-Driven PIPP......Page 295
 5 Real Hyperspectral Image Experiments......Page 296
  5.1 PIPP with Random Initial Conditions......Page 298
  5.2 PI-PRPP......Page 303
  5.3 ID-PIPP......Page 306
 6 Conclusions......Page 310
 References......Page 311