ENVI 监督分类Max stdev from Mean 参数IDL中的设置

通过设置class_doit 的参数 std_mult=3.0 即可。
完整代码如下：
参考引用：http://hi.baidu.com/dyqwrp/item/c8318cea9cec732c5a7cfbab

pro Parallelpiped_method
COMPILE_OPT idl2
;恢复ENVI_SAVE文件
ENVI,/restore_base_save_files
;开始批处理模式
ENVI_BATCH_INIT,log_file='batch.log'
;编写批处理过程
;选择文件

inputfile=   'E:\海二相关\掩膜\jpproject.img'

CATCH, Error_status
errorshow = 'Sorry to see the error,'+ $
' please send the error Information to "myyouthlife@163.com"'
IF Error_status NE 0 THEN BEGIN
tmp = DIALOG_MESSAGE(errorshow+STRING(13b)+$
!ERROR_STATE.MSG,/error,title = '错误提示!')
return
ENDIF
;输入数据预处理
ENVI_OPEN_FILE, inputfile, r_fid=fid
IF (fid EQ -1) THEN BEGIN
RETURN
ENDIF
;获取输入文件信息
ENVI_FILE_QUERY, fid, dims=dims, nb=nb
pos  = LINDGEN(nb)
;     输出分类图像名称
outputfile='d:\result.img'
out_name = outputfile
;-平行六面体分类  0
ENVI_RESTORE_ROIS, 'E:\海二相关\掩膜\11.roi'
;      获取感兴趣区文件信息
roi_ids = ENVI_GET_ROI_IDS(fid=fid, $
roi_colors=roi_colors, roi_names=class_names)
class_names = ['Unclassified', class_names]
num_classes = N_ELEMENTS(roi_ids)
; Set the unclassified class to black and use roi colors
lookup = BYTARR(3,num_classes+1)
lookup[0,1] = roi_colors
; 计算类ROI的基本统计信息
mean = FLTARR(N_ELEMENTS(pos), num_classes)
stdv = FLTARR(N_ELEMENTS(pos), num_classes)
cov = FLTARR(N_ELEMENTS(pos),N_ELEMENTS(pos),num_classes)
FOR j=0, num_classes-1 DO BEGIN
;
roi_dims=[ENVI_GET_ROI_DIMS_PTR(roi_ids[j]),0,0,0,0]
ENVI_DOIT, 'envi_stats_doit', fid=fid, pos=pos, $
dims=roi_dims, comp_flag=4, mean=c_mean, $
stdv=c_stdv, cov=c_cov
MEAN[0,j] = c_mean
stdv[0,j] = c_stdv
cov[0,0,j] = c_cov
ENDFOR
;设定阈值
thresh=REPLICATE(0.1,num_classes)
out_bname = 'parallelepiped'
;      分类
ENVI_DOIT, 'class_doit', fid=fid, pos=pos, dims=dims, $
out_bname=out_bname, out_name=out_name, method=0, $
mean=mean, stdv=stdv, std_mult=3.0, $
lookup=lookup, class_names=class_names, $
r_fid=r_fid,in_memory=0

;

;      退出批处理模式
;envi_batch_exit
end