多源遙感影像融合——基于脈沖耦合神經(jīng)網(wǎng)絡(luò)的方法
定 價(jià)：79 元
- 作者：李小軍 等
- 出版時(shí)間：2024/8/1
- ISBN：9787121485602
- 出 版 社：電子工業(yè)出版社
- 中圖法分類：TP751
- 頁碼：144
- 紙張：
- 版次：01
- 開本：16開
本書從多源遙感成像機(jī)理和人眼視覺對(duì)影像的理解出發(fā)，研究了結(jié)合PCNN 的配準(zhǔn)算法及基于PCNN 的全色影像、多光譜影像、高分辨率SAR 影像、無人機(jī)航拍影像和高光譜影像等多源遙感影像融合的理論與算法。首先，簡要介紹了多源遙感影像融合的起源與現(xiàn)狀。其次，回顧了PCNN 的幾種常見模型。鑒于遙感影像配準(zhǔn)是實(shí)現(xiàn)遙感影像像素級(jí)融合的前提，本書提出了兩種基于自適應(yīng)PCNN 分割的遙感影像配準(zhǔn)算法。在后續(xù)章節(jié)中，本書主要研究并提出了結(jié)合PCNN 分割特性的全色銳化融合算法、參數(shù)優(yōu)化的PCNN 全色銳化融合算法、改進(jìn)PCNN 的全色銳化融合模型、基于PCNN 的衛(wèi)星多光譜影像與無人機(jī)航拍影像融合算法和基于PCNN 的高光譜影像融合算法等。本書內(nèi)容為作者團(tuán)隊(duì)多年來取得的科研成果，涵蓋了基于PCNN 及其改進(jìn)模型在全色影像、多光譜影像、高分辨率SAR 影像、無人機(jī)航拍影像和高光譜影像等多源遙感影像融合中的最新成果。這些成果不僅豐富了遙感影像配準(zhǔn)與融合理論，也為相關(guān)領(lǐng)域的研究提供了借鑒與支持。
李小軍，理學(xué)博士，博士后，碩士生導(dǎo)師。曾工作于中國工程物理研究院電子工程研究所，任職副研究員�，F(xiàn)工作于蘭州交通大學(xué)測繪與地理信息學(xué)院，任職副教授。主持了多項(xiàng)軍委裝備發(fā)展部跨行業(yè)預(yù)研重點(diǎn)項(xiàng)目及國家自然科學(xué)基金項(xiàng)目。發(fā)表SCI、EI論文十余篇，獲批國家發(fā)明專利2項(xiàng)，研究領(lǐng)域主要包括遙感數(shù)字影像處理、影像融合和神經(jīng)網(wǎng)絡(luò)等。
目錄
第 1 章緒論··············································································································1
1.1 多源遙感影像融合的起源與發(fā)展······························································1
1.2 多源遙感影像融合的意義··········································································2
1.3 多源遙感影像融合研究現(xiàn)狀······································································4
1.3.1 傳統(tǒng)遙感影像全色銳化融合研究現(xiàn)狀·····················································4
1.3.2 基于視皮層神經(jīng)網(wǎng)絡(luò)的影像融合現(xiàn)狀·····················································5
1.4 多源遙感影像融合研究的關(guān)鍵問題··························································5
第2 章 PCNN 模型及特性······················································································7
2.1 PCNN 模型發(fā)展背景··················································································7
2.2 標(biāo)準(zhǔn)PCNN 模型·························································································9
2.2.1 PCNN 模型描述····················································································9
2.2.2 PCNN 模型特性·················································································.11
2.3 雙輸出PCNN（Dual-output PCNN，DPCNN）模型····························.11
2.3.1 DPCNN 模型描述···············································································12
2.3.2 DPCNN 模型特性···············································································14
2.4 彩色DPCNN（Color DPCNN，CDPCNN）模型··································.16
2.4.1 HSV 彩色空間····················································································16
2.4.2 CDPCNN 模型描述·············································································18
2.5 SAPCNN 模型··························································································.20
2.5.1 SAPCNN 模型設(shè)計(jì)·············································································20
2.5.2 SAPCNN 模型分析·············································································21
2.6 其他PCNN 相關(guān)模型··············································································.24
2.6.1 ICM 模型描述····················································································24
2.6.2 SCM 模型描述···················································································25
2.6.3 DQPCNN 模型描述·············································································25
2.7 本章小結(jié)··································································································.26
第3 章結(jié)合 PCNN 模型的遙感影像配準(zhǔn)····························································27
3.1 研究背景··································································································.28
3.2 遙感影像配準(zhǔn)國內(nèi)外研究現(xiàn)狀·······························································.28
3.2.1 基于區(qū)域的影像配準(zhǔn)算法····································································28
3.2.2 基于特征的影像配準(zhǔn)算法····································································29
3.3 基于自適應(yīng)PCNN 分割的遙感影像配準(zhǔn)算法·······································.31
3.3.1 算法總體框架·····················································································32
3.3.2 PCNN 影像分割··················································································32
3.3.3 參數(shù)自適應(yīng)PCNN 設(shè)計(jì)·······································································34
3.3.4 分割區(qū)域描述與匹配···········································································36
3.3.5 基于FSC 的配準(zhǔn)模型參數(shù)求解····························································39
3.3.6 實(shí)驗(yàn)與分析························································································40
3.4 基于PCNN 分割與點(diǎn)特征的多源遙感影像配準(zhǔn)算法···························.43
3.4.1 算法總體框架·····················································································44
3.4.2 UR-SIFT 點(diǎn)特征提取與匹配································································45
3.4.3 自適應(yīng)PCNN 分割區(qū)域匹配································································50
3.4.4 實(shí)驗(yàn)與分析························································································51
3.5 本章小結(jié)··································································································.58
第4 章 PCNN 分割特性與遙感影像全色銳化融合·············································59
4.1 研究背景··································································································.59
4.2 PCNN 遙感影像分割···············································································.59
4.3 PSBP 算法································································································.60
4.4 實(shí)驗(yàn)結(jié)果··································································································.62
4.4.1 實(shí)驗(yàn)數(shù)據(jù)···························································································62
4.4.2 評(píng)價(jià)指標(biāo)···························································································63
4.4.3 參數(shù)設(shè)置···························································································63
4.4.4 對(duì)比實(shí)驗(yàn)···························································································64
4.5 本章小結(jié)··································································································.68
第5 章 PCNN 參數(shù)優(yōu)化與遙感影像全色銳化融合·············································69
5.1 研究背景··································································································.69
5.2 SMA 自適應(yīng)PCNN 參數(shù)優(yōu)化算法·························································.70
5.3 實(shí)驗(yàn)結(jié)果··································································································.71
5.3.1 實(shí)驗(yàn)數(shù)據(jù)···························································································71
5.3.2 評(píng)價(jià)指標(biāo)···························································································72
5.3.3 對(duì)比實(shí)驗(yàn)···························································································72
5.3.4 SAR 影像與多光譜影像的融合實(shí)驗(yàn)結(jié)果···············································75
5.4 本章小結(jié)··································································································.77
第6 章遙感影像全色銳化融合模型·····································································78
6.1 研究背景··································································································.78
6.2 PPCNN 模型·····························································································.78
6.2.1 模型表達(dá)···························································································78
6.2.2 模型執(zhí)行···························································································80
6.2.3 PPCNN 模型在遙感影像融合中的應(yīng)用··················································81
6.3 全色銳化融合實(shí)驗(yàn)結(jié)果···········································································.82
6.3.1 實(shí)驗(yàn)數(shù)據(jù)集························································································82
6.3.2 參數(shù)設(shè)置···························································································83
6.3.3 對(duì)比實(shí)驗(yàn)···························································································84
6.4 雷達(dá)影像與光學(xué)影像實(shí)驗(yàn)·······································································.90
6.5 本章小結(jié)··································································································.92
第7 章基于 PCNN 的衛(wèi)星多光譜影像與無人機(jī)航拍影像融合·························93
7.1 研究背景··································································································.93
7.2 衛(wèi)星多光譜影像與無人機(jī)航拍影像融合算法········································.94
7.3 實(shí)驗(yàn)結(jié)果··································································································.95
7.3.1 實(shí)驗(yàn)數(shù)據(jù)集························································································95
7.3.2 PCNN 參數(shù)優(yōu)化··················································································96
7.3.3 融合質(zhì)量評(píng)價(jià)指標(biāo)··············································································97
7.3.4 對(duì)比實(shí)驗(yàn)···························································································97
7.4 本章小結(jié)··································································································.99
第8 章 PCNN 與高光譜影像融合······································································100
8.1 研究背景································································································.100
8.2 PCNN 與高光譜影像融合算法······························································.100
8.2.1 算法總體框架···················································································100
8.2.2 MSD-MCC 波段匹配·········································································101
8.2.3 IPCNN 模型·····················································································102
8.2.4 CSA 優(yōu)化IPCNN 關(guān)鍵參數(shù)································································104
8.2.5 提取影像細(xì)節(jié)···················································································105
8.2.6 自適應(yīng)細(xì)節(jié)注入與融合輸出·······························································106
8.3 實(shí)驗(yàn)結(jié)果································································································.107
8.3.1 實(shí)驗(yàn)數(shù)據(jù)集······················································································107
8.3.2 參數(shù)設(shè)置·························································································108
8.3.3 實(shí)驗(yàn)結(jié)果························································································.110
8.3.4 消融實(shí)驗(yàn)························································································.115
8.4 本章小結(jié)································································································.118
第9 章總結(jié)與展望·····························································································.119
9.1 多源遙感影像配準(zhǔn)與融合的研究總結(jié)··················································.119
9.2 多源遙感影像融合的發(fā)展趨勢·····························································.121
參考文獻(xiàn)··················································································································122
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