load?Indian_pines_corrected.mat;
load?Indian_pines_gt.mat;??%讀圖

[xyz]=size（indian_pines_corrected）;
data1=indian_pines_corrected（1:x1:y50）;
data2=indian_pines_corrected（1:x1:y100）;
data3=indian_pines_corrected（1:x1:y160）;
dataout（::1）=imadjust（uint16（data1））;
dataout（::2）=imadjust（uint16（data2））;
dataout（::3）=imadjust（uint16（data3））;

figure;
imshow（dataout）;
title（‘合成的假彩色顯示‘）;

[lwb]?=?size（indian_pines_corrected）;%l（length）圖像長度，w（width）圖像寬度，b（band）波段數?
c?=?max（max（indian_pines_gt））;%c（category）標準分類結果中的類別數
colormap_indian_pines?=?zeros（c3）;
colormap_indian_pines（1:）?=?[0.74510.74510.7451];%灰色
colormap_indian_pines（2:）?=?[010];%綠色
colormap_indian_pines（3:）?=?[001];%藍色
colormap_indian_pines（4:）?=?[00.54510];%深綠色
colormap_indian_pines（5:）?=?[10.647060];%橙色
colormap_indian_pines（6:）?=?[0.80390.521570.24706];%棕色
colormap_indian_pines（7:）?=?[0.62750.125490.94118];%紫色
colormap_indian_pines（8:）?=?[100];%紅色
colormap_indian_pines（9:）?=?[110];%黃色
colormap_indian_pines（10:）?=?[10.89410.76863];%橘黃色
colormap_indian_pines（11:）?=?[0.94111];%天藍色
colormap_indian_pines（12:）?=?[011];%青色
colormap_indian_pines（13:）?=?[10.8430];%金色
colormap_indian_pines（14:）?=?[101];%洋紅
colormap_indian_pines（15:）?=?[000.5019];%海軍藍
colormap_indian_pines（16:）?=?[110.87843];%淺黃色
pavia_truthmap?=?zeros（lw3）;%用于顯示的帕維亞大學標準分類結果
for?k?=?1:c
????for?i?=?1:l
????????for?j?=?1:w
????????????if?indian_pines_gt（ij）?==?k
????????????????pavia_truthmap（ij:）?=?colormap_indian_pines（k:）;?????????
????????????end
????????end
????end
end
figure;
imshow（pavia_truthmap[]）;title（‘真值圖顯示‘）;

indian_pines_corrected?=?myPCA（indian_pines_corrected）;??????%PCA降維
indian_pines_corrected?=?reshape（indian_pines_corrected145*145200）;????%將高光譜按波段排列
[indian_pines_corrected?maxV?minV]?=?scale（indian_pines_corrected?0?1）;??%歸一化處理，以便后續分類
indian_pines_gt?=?indian_pines_gt（:）;??????%數據按列排
[trainindexvalidindextestindex~]?=?SampleSelect（indian_pines_gt0.1）;?%?選擇10%的樣本作訓練

testindex?=?[testindex;validindex];?????%?其余的樣本作測試
TrainSamp?=?indian_pines_corrected（trainindex:）‘;%根據訓練樣本的標號找出訓練樣本
TestSamp?=?indian_pines_corrected（testindex:）‘;??%根據測試樣本的標號找出測試樣本
TrainLabel?=?indian_pines_gt（trainindex）;????%訓練樣本標簽
TestLabel?=?indian_pines_gt（testindex）;?????%測試樣本標簽

[bestcbestg]?=?GetcgCrossvalidate（TrainSampTrainLabel）;?%找到最優的SVM參數c和g
model?=?svmtrain（TrainLabelTrainSamp‘[‘-c?‘num2str（bestc）‘-g‘num2str（bestg）‘?-b?1?-q‘]）;???%訓練SVM分類器
disp（‘>?SVM?model?trained‘）;
[Labels~~]?=?svmpredict（TestLabelTestSamp‘model‘-b?1‘）;????????%SVM分類??????svmpredict和svmtrain都是MATLAB自帶的函數
Result?=?Confusmat（TestLabel?Labels）;??????????%計算混淆矩陣、總體分類精度、Kappa系數、生產者精度、用戶精度

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件???????2997??2019-05-15?09:01??高光譜\classification.m

?????文件???????1750??2019-05-14?09:02??高光譜\Confusmat.m

?????文件???????1125??2019-05-13?16:09??高光譜\fenlei.m

?????文件???????1517??2017-06-20?08:21??高光譜\GetcgCrossvalidate.m

?????文件??????36806??2019-05-13?23:24??高光譜\HSIclassificationGUI.fig

?????文件??????11356??2019-05-15?08:28??高光譜\HSIclassificationGUI.m

?????文件???????1701??2019-05-13?22:04??高光譜\HSIdisplay1.m

?????文件????5953527??2019-05-13?15:52??高光譜\Indian_pines_corrected.mat

?????文件???????1125??2019-05-13?15:52??高光譜\Indian_pines_gt.mat

?????文件????????556??2019-05-13?16:11??高光譜\jingdujiance.m

?????文件???????1497??2014-04-01?06:57??高光譜\libsvm-3.18\COPYRIGHT

?????文件??????78971??2014-04-01?06:57??高光譜\libsvm-3.18\FAQ.html

?????文件??????27670??2014-04-01?06:57??高光譜\libsvm-3.18\heart_scale

?????文件??????63803??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm\svm.java

?????文件??????63095??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm\svm.m4

?????文件????????868??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm\svm_model.java

?????文件????????115??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm\svm_node.java

?????文件???????1288??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm\svm_parameter.java

?????文件?????????87??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm\svm_print_interface.java

?????文件????????136??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm\svm_problem.java

?????文件??????51916??2014-04-01?06:57??高光譜\libsvm-3.18\java\libsvm.jar

?????文件????????624??2014-04-01?06:57??高光譜\libsvm-3.18\java\Makefile

?????文件???????4950??2014-04-01?06:57??高光譜\libsvm-3.18\java\svm_predict.java

?????文件???????8944??2014-04-01?06:57??高光譜\libsvm-3.18\java\svm_scale.java

?????文件??????12269??2014-04-01?06:57??高光譜\libsvm-3.18\java\svm_toy.java

?????文件???????8355??2014-04-01?06:57??高光譜\libsvm-3.18\java\svm_train.java

?????文件?????????81??2014-04-01?06:57??高光譜\libsvm-3.18\java\test_applet.html

?????文件????????732??2014-04-01?06:57??高光譜\libsvm-3.18\Makefile

?????文件???????1084??2014-04-01?06:57??高光譜\libsvm-3.18\Makefile.win

?????文件???????4069??2014-04-01?06:57??高光譜\libsvm-3.18\matlab\libsvmread.c

............此處省略65個文件信息