;-------------------------------------------------------------------------------------------------
; REMOVE THICK CLOUD IN SATELLITE IMAGES
;
; This code can be used for whole TM scene
; Developed and coded by Zhu Xiaolin
; Department of Geography,the Ohio State University
; Email:zhuxiaolin55@gmail.com
; updated：2017-11-21
; Debug history:
; 2013-10-23 correct:1) the bug of similar pixel searching
; 2) the bug of using wrong values in cloudy image
; 2017-11-21：correct a nonstop loop bug. It happens when processing large cloud patches and
; no similar pixel selected for a cloudy pixel
; 2021-05-09：correct a bug of similar pixel searching for line-shape clouds
;
; Please cite: Zhu, X., Gao, F., Liu, D. and Chen, J. A modified
; neighborhood similar pixel interpolator approach for removing
; thick clouds in Landsat images. IEEE Geoscience and Remote
; Sensing Letters, 2012, 9(3), 521-525
; NOTE: the efficiency may be low for large image.If so, please use CLOUD_REMOVE_FAST,
; in which some process was simplified, but the accuracy is still satisfactory
;-------------------------------------------------------------------------------------------------
;function of open file
Pro GetData,ImgData = ImgData,ns = ns,nl = nl,nb = nb,Data_Type = Data_Type,$
FileName = FileName,Map_info = map_Info, Fid = Fid
Filter = ['all file;*.*']
Envi_Open_File,FileName,R_Fid = Fid
Envi_File_Query,Fid,ns = ns,nl = nl,nb = nb,Data_Type = Data_Type
map_info = envi_get_map_info(fid=Fid)
dims = [-1,0,ns - 1 ,0,nl - 1]
case Data_Type Of
1:ImgData = BytArr(ns,nl,nb) ; BYTE Byte
2:ImgData = IntArr(ns,nl,nb) ; INT Integer
3:ImgData = LonArr(ns,nl,nb) ; LONG Longword integer
4:ImgData = FltArr(ns,nl,nb) ; FLOAT Floating point
5:ImgData = DblArr(ns,nl,nb) ; DOUBLE Double-precision floating
6:ImgData = COMPLEXARR(ns,nl,nb); complex, single-precision, floating-point
9:ImgData = DCOMPLEXARR(ns,nl,nb);complex, double-precision, floating-point
12:ImgData = UINTARR(ns,nl,nb) ; unsigned integer vector or array
13:ImgData = ULONARR(ns,nl,nb) ; unsigned longword integer vector or array
14:ImgData = LON64ARR(ns,nl,nb) ;a 64-bit integer vector or array
15:ImgData = ULON64ARR(ns,nl,nb) ;an unsigned 64-bit integer vector or array
EndCase
For i = 0,nb-1 Do Begin
Dt = Envi_Get_Data(Fid = Fid,dims = dims,pos=i)
ImgData[*,*,i] = Dt[*,*]
EndFor
End
;-------------------------------------------------------------------
; main body of the program
;-------------------------------------------------------------------
pro CLOUD_REMOVE
t0=systime(1)
;set parameters
;------------------------------------------------
num_class=4 ;set the estimated number of classes in image
min_pixel=20 ;set the sample size of similar pixels
extent1=1 ;set the range of cloud neighborhood
DN_min=0.0 ;set the range of DN
DN_max=1.0
patch_long=500 ;set the block size when process large images, 500~1000 recommend
;-------------------------------------------------
FileName1 = Dialog_PickFile(title = 'Open the cloudy image:')
envi_open_file,FileName1,r_fid=fid
envi_file_query,fid,ns=ns,nl=nl,nb=nb,dims=dims
map_info = envi_get_map_info(fid=fid)
orig_ns=ns
orig_nl=nl
n_ns=ceil(float(ns)/patch_long)
n_nl=ceil(float(nl)/patch_long)
ind_patch=intarr(4,n_ns*n_nl)
for i_ns=0,n_ns-1,1 do begin
for i_nl=0,n_nl-1,1 do begin
ind_patch[0,n_ns*i_nl+i_ns]=i_ns*patch_long
ind_patch[1,n_ns*i_nl+i_ns]=min([ns-1,(i_ns+1)*patch_long-1])
ind_patch[2,n_ns*i_nl+i_ns]=i_nl*patch_long
ind_patch[3,n_ns*i_nl+i_ns]=min([nl-1,(i_nl+1)*patch_long-1])
endfor
endfor
temp_file=FileName1
tempoutname=temp_file+'_temp_cloud'
pos=indgen(nb)
for isub=0,n_ns*n_nl-1,1 do begin
dims=[-1,ind_patch[0,isub],ind_patch[1,isub],ind_patch[2,isub],ind_patch[3,isub]]
envi_doit, 'resize_doit', fid=fid, pos=pos, dims=dims, interp=0, rfact=[1,1], $
out_name=tempoutname+strtrim(isub+1,1), r_fid=r_fid1
envi_file_mng, id=r_fid1, /remove
endfor
envi_file_mng, id=fid, /remove
;-----------------------------------------------------------
FileName2 = Dialog_PickFile(title = 'Open the input clear image:')
envi_open_file,FileName2,r_fid=fid
tempoutname=temp_file+'_temp_clear'
pos=indgen(nb)
for isub=0,n_ns*n_nl-1,1 do begin
dims=[-1,ind_patch[0,isub],ind_patch[1,isub],ind_patch[2,isub],ind_patch[3,isub]]
envi_doit, 'resize_doit', fid=fid, pos=pos, dims=dims, interp=0, rfact=[1,1], $
out_name=tempoutname+strtrim(isub+1,1), r_fid=r_fid1
envi_file_mng, id=r_fid1, /remove
endfor
envi_file_mng, id=fid, /remove
;------------------------------------------------------------
FileName3 = Dialog_PickFile(title = 'Open the cloud mask image:')
envi_open_file,FileName3,r_fid=fid
tempoutname=temp_file+'_temp_cloud_mask'
pos=indgen(1)
for isub=0,n_ns*n_nl-1,1 do begin
dims=[-1,ind_patch[0,isub],ind_patch[1,isub],ind_patch[2,isub],ind_patch[3,isub]]
envi_doit, 'resize_doit', fid=fid, pos=pos, dims=dims, interp=0, rfact=[1,1], $
out_name=tempoutname+strtrim(isub+1,1), r_fid=r_fid1
envi_file_mng, id=r_fid1, /remove
endfor
envi_file_mng, id=fid, /remove
;-------------------------------------------------------------------
tempoutname=temp_file+'_temp_filled'
print,'there are total',n_ns*n_nl,'patches'
for isub=0,n_ns*n_nl-1,1 do begin
;open each block
FileName = temp_file+'_temp_cloud'
GetData,ImgData=ImgData,ns = ns1,nl = nl1,nb = nb,Data_Type = Data_Type,FileName = FileName+strtrim(isub+1,1),Fid = Fid1
fine1=ImgData
FileName = temp_file+'_temp_clear'
GetData,ImgData=ImgData,ns = ns2,nl = nl2,nb = nb,FileName = FileName+strtrim(isub+1,1),Fid = Fid2
fine2=ImgData
FileName = temp_file+'_temp_cloud_mask'
GetData,ImgData=ImgData,FileName = FileName+strtrim(isub+1,1),Fid = Fid3
cloud=ImgData
;-----------------------------------------------------------------------
cloud_posite=where(cloud ne 0,c_c)
if (c_c gt 0) then begin
num_cloud_path=max(cloud[cloud_posite])
;
for icloud=1,num_cloud_path,1 do begin ; remove each cloud patches
cloud_area=where(cloud eq icloud,num_cloud1)
if (num_cloud1 gt 0) then begin
cloud_pixel_locate=intarr(2,num_cloud1)
cloud_pixel_locate[1,*]=fix(cloud_area/ns1)
cloud_pixel_locate[0,*]=cloud_area-ns1*cloud_pixel_locate[1,*]
left_cloud=min(cloud_pixel_locate[0,*]) ;find out the cloud area
right_cloud=max(cloud_pixel_locate[0,*])
up_cloud=min(cloud_pixel_locate[1,*])
down_cloud=max(cloud_pixel_locate[1,*])
cloud_area=0 ;clear it
cloud_pixel_locate=0 ;clear it
;neigborhood of cloud area: rectangle which can completely cover cloud
left_region=max([0,left_cloud-extent1])
right_region=min([ns1-1,right_cloud+extent1])
up_region=max([0,up_cloud-extent1])
down_region=min([nl1-1,down_cloud+extent1])
a_region=right_region-left_region+1
b_region=down_region-up_region+1
x_center=a_region/2.0 ; the position of cloud center
y_center=b_region/2.0
sub_fine1=fine1[left_region:right_region,up_region:down_region,*]
sub_fine2=fine2[left_region:right_region,up_region:down_region,*]
sub_cloud=cloud[left_region:right_region,up_region:down_region]
;---------------------remove background-----------------
fine1_value=sub_cloud
fine1_value[*,*]=0
fine2_value=fine1_value
for ib=0,nb-1,1 do begin
fine1_value=mean(fine1_value+sub_fine1[*,*,ib])
fine2_value=mean(fine2_value+sub_fine2[*,*,ib])
endfor
ind_com=where(fine1_value eq 0 or fine2_value eq 0, c_com)
if (c_com gt 0) then begin
sub_cloud[ind_com]=-1 ;mask out background
endif
fine1_value=0
fine2_value=0
similar_th_band=fltarr(nb)
for iband=0,nb-1,1 do begin
similar_th_band[iband]=stddev(sub_fine2[*,*,iband])*2.0/float(num_class) ;compute the threshold of similar pixel
endfor
ind_cloud=where(sub_cloud eq icloud,num_cloud)
ind_clear=where(sub_cloud eq 0,num_clear)
xy_clear=fltarr(2,num_clear) ;the location of each clear pixel
xy_clear[1,*]=fix(ind_clear/(a_region))
xy_clear[0,*]=ind_clear-(a_region)*xy_clear[1,*]
fine2_clear=fltarr(num_clear,nb)
fine1_clear=fltarr(num_clear,nb)
for ib=0,nb-1,1 do begin
fine2_clear[*,ib]=(sub_fine2[*,*,ib])[ind_clear]
fine1_clear[*,ib]=(sub_fine1[*,*,ib])[ind_clear]
endfor
for ic=0.0,num_cloud-1.0,1.0 do begin
ri=float(fix(ind_cloud[ic]/(a_region))) ; the location of target pixel
ci=float(ind_cloud[ic]-(a_region)*ri)
center_dis=((x_center-ci)^2+(y_center-ri)^2)^0.5; the distance between target pixel and center of cloud
s_dis=((xy_clear[0,*]-ci)^2+(xy_clear[1,*]-ri)^2)^0.5
sub_on_common=fltarr(num_clear,nb)
for iband=0,nb-1,1 do begin
sub_on_common[*,iband]= fine2_clear[*,iband]-sub_fine2[ci,ri,iband]
endfor
rmsei=mean(sub_on_common^2,DIMENSION=2)^0.5+0.0001
order_clear=sort(rmsei,/L64) ;order all common pixels by rmse with the target pixel
iclear=0.0
isimilar=0.0
fine1_similar=fltarr(min_pixel,nb)
fine2_similar=fltarr(min_pixel,nb)
rmse_similar=fltarr(min_pixel)
dis_similar=fltarr(min_pixel)
similar_rmse12=fltarr(min_pixel)
maxi_num_seach=min([num_clear,20.0*min_pixel]) ;limit the searching pixels to increase the efficiency
while (isimilar le min_pixel-1 and iclear le maxi_num_seach-1.0 ) do begin
indicate_similar=0
for iband=0,nb-1,1 do begin
if (abs(fine2_clear[order_clear[iclear],iband]-sub_fine2[ci,ri,iband])le similar_th_band[iband]) then begin
indicate_similar=indicate_similar+1
endif
endfor
if (indicate_similar eq nb) then begin
for ib=0, nb-1,1 do begin
fine1_similar[isimilar,ib]=(fine1_clear[*,ib])[order_clear[iclear]]
fine2_similar[isimilar,ib]=(fine2_clear[*,ib])[order_clear[iclear]]
endfor
rmse_similar[isimilar]=((total((fine2_clear[order_clear[iclear],*]-sub_fine2[ci,ri,*])^2))/float(nb))^0.5
dis_similar[isimilar]=s_dis[order_clear[iclear]]
similar_rmse12[isimilar]=((total((fine2_clear[order_clear[iclear],*]-fine1_clear[order_clear[iclear],*])^2))/float(nb))^0.5
isimilar=isimilar+1
endif
iclear=iclear+1.0
endwhile
; if similar pixel larger than 0
if (isimilar gt 0 ) then begin
ind_null=where(dis_similar gt 0)
rmse_similar1=(rmse_similar[ind_null]-min(rmse_similar[ind_null]))/(max(rmse_similar[ind_null])-min(rmse_similar[ind_null])+0.000001)+1.0
dis_similar1=(dis_similar[ind_null]-min(dis_similar[ind_null]))/(max(dis_similar[ind_null])-min(dis_similar[ind_null])+0.000001)+1.0
C_D=(rmse_similar1)*dis_similar1+0.0000001
weight=(1.0/C_D)/total(1.0/C_D)
;compute the time weight
W_T1=center_dis/(center_dis+mean(dis_similar[ind_null]))
W_T2=mean(dis_similar[ind_null])/(center_dis+mean(dis_similar[ind_null]))
for iband=0,nb-1,1 do begin
predict_1=total((fine1_similar[*,iband])[ind_null]*weight)
predict_2=sub_fine2[ci,ri,iband]+total(((fine1_similar[*,iband])[ind_null]-(fine2_similar[*,iband])[ind_null])*weight)
if (predict_2 gt DN_min and predict_2 lt DN_max) then begin
sub_fine1[ci,ri,iband]=W_T1*predict_1+W_T2*predict_2
endif else begin
sub_fine1[ci,ri,iband]=predict_1
endelse
endfor
endif else begin
; if no similar pixel, use all similar pixels
for iband=0,nb-1,1 do begin
diff=mean(fine1_clear[*,iband]-fine2_clear[*,iband])
sub_fine1[ci,ri,iband]=sub_fine2[ci,ri,iband]+diff
endfor
endelse
endfor
fine1[left_region:right_region,up_region:down_region,*]=sub_fine1
endif
endfor
endif
print,'finished ',isub+1,' patch'
;
Envi_Write_Envi_File,fine1,Out_Name = tempoutname+strtrim(isub+1,1)
envi_file_mng, id=Fid1, /remove, /delete
envi_file_mng, id=Fid2, /remove, /delete
envi_file_mng, id=Fid3, /remove, /delete
endfor
;--------------------------------------------------------------------------------------
;mosiac all the filled patch
mfid=intarr(n_ns*n_nl)
mdims=intarr(5,n_ns*n_nl)
mpos=intarr(nb,n_ns*n_nl)
pos=indgen(nb)
x0=intarr(n_ns*n_nl)
y0=intarr(n_ns*n_nl)
for isub=0,n_ns*n_nl-1,1 do begin
envi_open_file, tempoutname+strtrim(isub+1,1), r_fid= sub_fid
if (sub_fid eq -1) then begin
envi_batch_exit
return
endif
envi_file_query, sub_fid, ns=sub_ns, nl=sub_nl
mfid[isub] = sub_fid
mpos[*,isub] = indgen(nb)
mdims[*,isub] = [-1,0, sub_ns-1,0, sub_nl-1]
x0[isub]=ind_patch[0,isub]
y0[isub]=ind_patch[2,isub]
endfor
xsize = orig_ns
ysize = orig_nl
pixel_size = [1.,1.]
use_see_through = replicate(1L,n_ns*n_nl)
see_through_val = replicate(0L,n_ns*n_nl)
; out_name=Dialog_PickFile(Title = 'Enter the filename of the restored image')
out_name=FileName1+'cloud_remove'
envi_doit, 'mosaic_doit', fid=mfid, pos=mpos, $
dims=mdims, out_name=out_name, xsize=xsize, $
ysize=ysize, x0=x0, y0=y0, georef=0,MAP_INFO=map_info, $
out_dt=Data_Type, pixel_size=pixel_size, $
background=0, see_through_val=see_through_val, $
use_see_through=use_see_through
for i=0,n_ns*n_nl-1,1 do begin
envi_file_mng, id=mfid[i], /remove, /delete
endfor
print, 'time used', floor((systime(1)-t0)/3600), 'hour',floor(((systime(1)-t0) mod 3600)/60),'m',(systime(1)-t0) mod 60,'s'
end这是完整代码，代码运行的环境是ENVI5.6和IDL 8.8.0 (Win32 x86_64 m64).，根据这些信息解决上面的问题
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