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MatchCloudShadow.m
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MatchCloudShadow.m
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This functin is used to match cloud shadow with cloud.
% The similarity defineing cloud shadow is larger than 0.3 only for those
% clouds, of which all pixels are included in the Landsat observations.
% This minor modification was made because the match similarity may be
% wrong when some parts of cloud are out of the observations.
%
%
% set static seed for random generator. By Shi, at 27 Jan., 2022
% mask out the shadow of cloud over water or not? By Shi, at 17, March, 2020
% fix the bug that cloud shadow would be projected on the other side in Sentinel-2 imagery when the azimuth angle > 180. By Shi, at 19, Jan., 2019
% use new match similarity becasue we do not know the potential clouds
% excluding self cloud and outsides are shadow or not. by Shi, at 21, April, 2018
% remove the overlap between final matched cloud shadow and the potential
% cloud shadow. by Shi, at 26, Mar., 2018.
% speed up the match of cloud shadow with cloud for large clouds using
% sampling projections. by Zhe and Shi. at 24, Mar., 2018.
% do not revisit for the big clouds (more than 10,000,000). by Shi. at 22, Mar., 2018
% match cloud shadow by following the sort from the center because the
% clouds loacted boundary will be easily affected due to the unkown of the
% pixels out of obervations. by Shi. at 15, Mar., 2018
% cloud's temperature may be warmer than surface when we wrongly give some
% surface to the cloud. This will result in no cloud shadow. by Shi. at 3, Mar., 2018
% fix the bugger that revisit clouds when less than 14 cloud objects. by Shi. at 11, Dec., 2017
% still improve the prediction of cloud shadow location when no DEMs. by Shi. at 13, Sept., 2017
% revisit the first 14 cloud objects. by Shi. at 21,Feb.,2017
% fix the bugger, struct2table for lt. struct2table. at 21,Feb.,2017
% search neighboring clouds by distance rule. by Shi. at 13,Feb.,2017
% fix the bugger that bias for the location of real cloud object. at 13,Oct.,2016
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ similar_num,data_cloud_matched, data_shadow_matched] = MatchCloudShadow(...
mask,plcim,plsim,isShadowater,waterAll,data_dem,data_bt_c,t_templ,t_temph,data_meta,ptm,num_near,angles_view)
dim=data_meta.Dim;
% get potential mask values
data_shadow_potential=zeros(dim,'uint8');
data_cloud_potential=(plcim>0)&mask==1;
data_shadow_potential(plsim==1)=1;% plshadow layer
clear plsim; % empty memory
% matched cloud & shadow layer
data_cloud_matched=zeros(dim,'uint8');
data_shadow_matched=zeros(dim,'double');
% revised percent of cloud on the scene after plcloud
revised_ptm=sum(data_cloud_potential(:))/sum(mask(:));
% When having too many clouds, we will not match cloud shadow.
if ptm <=40000||revised_ptm>=0.90 % 0.1% was changed to 40,000 pixels.
fprintf('Skip cloud shadow detection because high cloud cover\n');
data_cloud_matched(data_cloud_potential==true)=1;
data_shadow_matched(data_shadow_potential==false)=1;
data_shadow_matched=uint8(data_shadow_matched);
similar_num=-1;
else
clear pfpl;
%% parameters
clear plcim; % empty memory
% max similarity threshold
max_similar = 0.95;
% number of inward pixes (240m) for cloud base temperature
num_pix=3;
% enviromental lapse rate 6.5 degrees/km
rate_elapse=6.5;
% dry adiabatic lapse rate 9.8 degrees/km
rate_dlapse=9.8;
% max match pixels number
max_match_num =1000000; %more than 1 million pixels will result in ~2 mins runtime.
% sun angles
sun_zenith_deg=data_meta.Zen;
sun_azimuth_deg=data_meta.Azi;
% sun angle geometry
sun_elevation_deg=90-sun_zenith_deg;
sun_elevation_rad=deg2rad(sun_elevation_deg);
% solar azimuth anngle
Sun_tazi=sun_azimuth_deg-90;
sun_tazi_rad=deg2rad(Sun_tazi);
clear sun_elevation_deg sun_elevation_deg;
% view angles for Sentinel 2 images, which will be used compute the
% average values for each cloud. Note that the Landsat's view angles
% can be estimated by the obersations of the entire scene.
if strcmp(data_meta.Sensor,'S_MSI')
VAA = angles_view.VAA;
VZA = angles_view.VZA ;
clear angles_view;
% mini matched similarity
Tsimilar=0.425;
% Tsimilar=0.4;
% threshold for matching buffering
Tbuffer=0.90;
elseif strcmp(data_meta.Sensor,'L_OLI_TIRS')||...
strcmp(data_meta.Sensor,'L_ETM_PLUS')||...
strcmp(data_meta.Sensor,'L_TM')
% mini matched similarity
% Tsimilar=0.35;
Tsimilar=0.3;
% threshold for matching buffering
Tbuffer=0.95;
% view angle geometry for Landsat
% get track derection
[rows,cols]=find(mask==1);
[cor_ul_y,num]=min(rows);cor_ul_x=cols(num);
[cor_lr_y,num]=max(rows);cor_lr_x=cols(num);
[cor_ll_x,num]=min(cols);cor_ll_y=rows(num);
[cor_ur_x,num]=max(cols);cor_ur_y=rows(num);
% get view angle geometry
[A,B,C,omiga_par,omiga_per]=getSensorViewGeo(cor_ul_x,cor_ul_y,cor_ur_x,cor_ur_y,cor_ll_x,cor_ll_y,cor_lr_x,cor_lr_y);
clear cor_ul_x cor_ul_y cor_ur_x cor_ur_y cor_ll_x cor_ll_y cor_lr_x cor_lr_y;
else
error('Only Landsats 4-7, Landsat 8 and Sentinel 2 data can be supported./n');
end
% the lowest elevation.
if ~isempty(data_dem)
dem_base_heigh=double(prctile(data_dem(mask),0.001));
else
dem_base_heigh=0;
end
% expand 1,000 pixels for the potential cloud shadow layer.
dim_expd=2000;
% spatial resolution of the image
sub_size=data_meta.Resolution(1);
win_height=dim(1);win_width=dim(2);
% intervals within each matching process.
step_interval=2*sub_size*tan(sun_elevation_rad);
%% project all potential cloud shadow and cloud (can be matched) along sun light based on DEMs.
% cloud shadow may be overlap with another cloud, so we need to
% project the all potential cloud and potential cloud shadow pixels.
[recorderRow,recorderCol] = ProjectDEM2Plane(dim,...
mask,...
data_dem,dem_base_heigh,sun_elevation_rad,sun_tazi_rad,...
sun_azimuth_deg,dim_expd,...
data_meta.Resolution);
% create cloud objtects using 8-by-8 pixels connection.
[segm_cloud,num]=bwlabeln(data_cloud_potential,8);
s = regionprops(segm_cloud,'area');
area_final = [s.Area];
obj_num=area_final;
clear segm_cloud_init L idx area_final s;
% Get the x,y of each cloud
% Matrix used in recording the x,y
stats= regionprops(segm_cloud,'Centroid','PixelList');
match_clds=zeros(1,num,'uint8'); % cloud shadow match similarity (m)
matched_clds_centroid=[]; % centers of cloud having shadow
height_clds_recorder=[]; % cloud shadow match heights (m)
% Use iteration to get the optimal move distance
% Calulate the moving cloud shadow
similar_num=zeros(1,num); % cloud shadow match similarity (m)
l_pt=0.175; h_pt=1-l_pt;
dim_expand=dim+2*dim_expd;
record_base_h_num=0;
num_revisited = 0;
if num > num_near
num_revisited=num_near;
end
num_all=num+num_revisited;
% min moving distance (min high 200 meters) unit: pixels
i_xy_min=200/(sub_size*tan(sun_elevation_rad));
for cloud_type_cur= 1:num_all %num
% revisit the first 14 cloud objects.
cloud_type=cloud_type_cur;
if cloud_type>num && num_revisited<num
cloud_type=cloud_type_cur - num; % fix this bug.
end
% moving cloud xys
XY_type_all=zeros(obj_num(cloud_type),2);
% % record the max threshold moving cloud xys
% tmp_XY_type_all=zeros(obj_num(cloud_type),2);
% corrected for view angle xys
tmp_xys_all=zeros(obj_num(cloud_type),2);
% record the original xys
orin_xys_all=zeros(obj_num(cloud_type),2);
% record the original xys
orin_xys_all(:,:)=stats(cloud_type,:).PixelList(:,:);
% record this orinal ids
orin_cid_all=sub2ind(dim,orin_xys_all(:,2),orin_xys_all(:,1));
% assume object is round r_obj is radium of object
r_obj=sqrt(obj_num(cloud_type)/2*pi);
% refine cloud height range (m)
% initialize height and similarity info
if isempty(data_dem)
base_heigh_cloud=0;
else
% if the above rule removed all pixels, back to MFmask.
dem_base_cloud=data_dem(orin_cid_all);
% The min height should be the max dem of dem_base_cloud.
% However, the commission error from snow may lead to overestimate the base heigh.
base_heigh_cloud=prctile(dem_base_cloud,100*h_pt)-dem_base_heigh;
clear dem_base_cloud;
end
% Min cloud base height (m)
Min_cl_height=200.00 + base_heigh_cloud; % 2738
% Max cloud base height (m)
Max_cl_height=12000.00 + base_heigh_cloud;
if ~isempty(data_bt_c) % if have no temperature data.
% Temperature of the cloud object
temp_obj_all=data_bt_c(orin_cid_all);
% the base temperature for cloud
% number of inward pixes for correct temperature
% num_pix=8;
pct_obj=(r_obj-num_pix)^2/r_obj^2;
pct_obj=min(pct_obj,1); % pct of edge pixel should be less than 1
t_obj=quantile(temp_obj_all(:),pct_obj);
clear pct_obj;
t_obj=double(t_obj);
% put the edge of the cloud the same value as t_obj
temp_obj_all(temp_obj_all>t_obj)=t_obj;
if ~(t_templ<t_obj||t_temph<t_obj) % cloud's temperature may be warmer than surface when we wrongly give some surface to the cloud.
Min_cl_height=max(Min_cl_height,10*(t_templ-400-t_obj)/rate_dlapse);
Max_cl_height=min(Max_cl_height,10*(t_temph+400-t_obj));
end
end
% when reaching big clouds, the max bias for cloud shadow will
% be estimated, but exclude dem info.
if obj_num(cloud_type) > max_match_num
% renew the arrays
% randomly selection.
rng(1);% static seed
samples_rand_all=randperm(obj_num(cloud_type));
samples_mov=samples_rand_all(1:max_match_num);
clear samples_rand_all;
% moving cloud xys
XY_type=XY_type_all(samples_mov,:);
% corrected for view angle xys
tmp_xys=tmp_xys_all(samples_mov,:);
% record this orinal ids
orin_xys = orin_xys_all(samples_mov,:);
% orin_xys = orin_xys_all(samples_mov,1);
if ~isempty(data_bt_c) % if have no temperature data.
% Temperature of the cloud object
temp_obj=temp_obj_all(samples_mov);
end
else
% give all pixels
% moving cloud xys
XY_type=XY_type_all;
% corrected for view angle xys
tmp_xys=tmp_xys_all;
% record the original xys
orin_xys=orin_xys_all;
% record this orinal ids
% orin_cid=orin_cid_all;
if ~isempty(data_bt_c) % if have no temperature data.
% temperature
temp_obj=temp_obj_all;
end
end
% record_h=0;
record_thresh=0;
record_base_h=0;
record_base_h_near=0;% it is available only when >0
center_cur=stats(cloud_type,:).Centroid;
if strcmp(data_meta.Sensor,'S_MSI')
VZAxy = pi/180*mean(single(VZA(orin_cid_all))/100);
VAAxy = pi/180*mean(single(VAA(orin_cid_all))/100);
end
% height estimated by neighboring clouds.
if record_base_h_num>=num_near
% the centers of already matched clouds
% current cloud's center
% the nearest cloud among all matched clouds.
% remove the self cloud heigh
[nearest_cloud_centers,nearest_dis]=knnsearch(matched_clds_centroid,center_cur,'k',num_near, 'distance','cityblock');% less time-consuming method chebychev
if cloud_type_cur>num % remove its self for the first 14 clouds when coming back.
nearest_cloud_centers(nearest_dis==0)=[];
end
% get all matched clouds' height.
record_base_h_tmp=height_clds_recorder(nearest_cloud_centers);
record_base_h_near=prctile(record_base_h_tmp,100*h_pt);
h_pre_std=std(record_base_h_tmp);
clear record_base_h_tmp;
if h_pre_std>=1000||record_base_h_near <= Min_cl_height||record_base_h_near >= Max_cl_height
record_base_h_near=0;
end
clear h_pre_std;
end
dist_pre=0;
dist_passed=false;
dist_first=true;
% all pixels of projected cloud object
if numel(orin_cid_all(:))==0
dist_passed=true;
else
cpc_i=center_cur(2);
cpc_j=center_cur(1);
end
% indicates the number of the matched cloud shadows for this
% current cloud.
num_matched=0;
for base_h=Min_cl_height:step_interval:Max_cl_height % iterate in height (m)
% Get the true postion of the cloud
% calculate cloud DEM with initial base height
if strcmp(data_meta.Sensor,'S_MSI')
h=base_h; % have no temperature data. cannot serve as 3D object.
elseif strcmp(data_meta.Sensor,'L_OLI_TIRS')||...
strcmp(data_meta.Sensor,'L_ETM_PLUS')||...
strcmp(data_meta.Sensor,'L_TM')
h=double(10*(t_obj-temp_obj)/rate_elapse+base_h);% relative to the reference plane. Cloud top's height.
end
% the height for the bias of the real cloud location should exclude the
% surface elevation below the cloud object.
h_bias=h-base_heigh_cloud;% hc-Ec the height between cloud object and its surface.
if strcmp(data_meta.Sensor,'S_MSI')
[tmp_xys(:,1),tmp_xys(:,2)]= getRealCloudPositionS2(orin_xys(:,1),...
orin_xys(:,2),h_bias,VZAxy,VAAxy,data_meta.Resolution);
elseif strcmp(data_meta.Sensor,'L_OLI_TIRS')||...
strcmp(data_meta.Sensor,'L_ETM_PLUS')||...
strcmp(data_meta.Sensor,'L_TM')
sensor_heigh_bias=base_heigh_cloud+dem_base_heigh; % used to exclude the elevation of cloud' surface.
[tmp_xys(:,1),tmp_xys(:,2)]=getRealCloudPosition(orin_xys(:,1),...
orin_xys(:,2),h_bias,A,B,C,omiga_par,omiga_per,sensor_heigh_bias);
else
error('Only Landsats 4-7, Landsat 8 and Sentinel 2 data can be supported./n');
end
% shadow moved distance (pixel) to calculate the cloud
% shadow locaiton.
% real cloud height relative to the plane.
i_xy=h/(sub_size*tan(sun_elevation_rad));
XY_type(:,2)=round(tmp_xys(:,1)-i_xy*cos(sun_tazi_rad)); % X is for j,2
XY_type(:,1)=round(tmp_xys(:,2)-i_xy*sin(sun_tazi_rad)); % Y is for i,1
clear i_xy;
% this location is relative to reference plane.
tmp_j_plane=XY_type(:,2);% col
tmp_i_plane=XY_type(:,1);% row
clear XY_type;
% back project
% dim_expd=1000;% 1000 pixels buffer
% some projected pixels out of observations.
tmp_i_plane_expd_tmp=tmp_i_plane+dim_expd;
tmp_j_plane_expd_tmp=tmp_j_plane+dim_expd;
avail_pixels=find(tmp_i_plane_expd_tmp>0&tmp_j_plane_expd_tmp>0&...
tmp_i_plane_expd_tmp<=dim_expand(1)&tmp_j_plane_expd_tmp<=dim_expand(2));
tmp_i_plane_expd=tmp_i_plane_expd_tmp(avail_pixels);
tmp_j_plane_expd=tmp_j_plane_expd_tmp(avail_pixels);
clear tmp_i_plane_expd_tmp tmp_j_plane_expd_tmp avail_pixels;
tmp_id_plane_expd=sub2ind(dim_expand,tmp_i_plane_expd,tmp_j_plane_expd); % matched shadow locations
clear tmp_i_plane_expd tmp_j_plane_expd;
% search the responding locations in real surface (derived
% from the relation-lookup table).
tmp_i_obs=recorderRow(tmp_id_plane_expd);
tmp_j_obs=recorderCol(tmp_id_plane_expd);
clear tmp_id_plane_expd tmp_id_plane_expd;
% cloud shadow must be beyond the location of the orgianl cloud.
if ~dist_passed
% the center of cloud shadow in real image.
sum_cpmp_i=sum(tmp_i_obs(:));
sum_cpmp_j=sum(tmp_j_obs(:));
area_cpmp=numel(tmp_j_obs(:));
ctmp_i=sum_cpmp_i/area_cpmp;
ctmp_j=sum_cpmp_j/area_cpmp;
clear sum_cpmp_i sum_cpmp_j area_cpmp;
% distance between orginal cloud and its cloud shadow,
% Note we ignored the mini bias from view angles here.
dist_cur = pdist2([ctmp_j,ctmp_i],[cpc_j,cpc_i],'Euclidean');
% dist_cur = floor(dist_cur);
clear ctmp_j ctmp_i;
if dist_first
dist_pre = dist_cur;
dist_first = false;
else
% the distance between the center of cloud and
% cloud shadow over plane decreases
if dist_pre >= dist_cur || dist_cur<i_xy_min % should move more than 200 meter high.
dist_pre = dist_cur;
record_thresh = 0;
% record_h=0;
continue;
else
dist_passed = true; % can go
end
end
end
% calculate the similarity for the matched cloud shadow.
% the id that is out of the entire image
% out-of-scene pixels should be found. the relationship
% between locations at plane and DEM is lack.
out_id=(tmp_i_obs<1|tmp_i_obs>win_height|tmp_j_obs<1|tmp_j_obs>win_width);
out_all=sum(out_id(:));
% exclude the pixels out of the entire image.
tmp_ii_obs=tmp_i_obs(out_id==0);
tmp_jj_obs=tmp_j_obs(out_id==0);
clear out_id tmp_i_obs tmp_j_obs;
tmp_id=sub2ind(dim,tmp_ii_obs,tmp_jj_obs); % matched shadow locations
clear tmp_ii_obs tmp_jj_obs;
out_obs=mask(tmp_id)==0;
id_ex_self = segm_cloud(tmp_id)~=cloud_type;
% 1st rule: out of obervations; 2nd rule: located in
% potential shadow or other clouds (exclude the self cloud).
% Special case #1:
% for the cloud shadow previoudly matched, the new one
% cannot reach the boundary and other clouds, which easily
% result in the overestimation of silimarity.
match_id_unsure = out_obs | ...
(id_ex_self&(data_cloud_potential(tmp_id)==1));
match_id_sure = id_ex_self&data_shadow_potential(tmp_id)==1;
% we do not provide the cloud shadow for the clouds over water
% when shadow is 100% over water, stop to match cloud
% shadow.
if ~isShadowater && sum(waterAll(tmp_id))==length(tmp_id)
break;
end
% give half weight to the macthed pixels located in outside and other
% clouds.
matched_all=sum(match_id_sure(:))+0.5*sum(match_id_unsure(:))+out_all;
total_all=sum(id_ex_self(:))+out_all;
thresh_match=matched_all/total_all;
clear match_id total_all;
% used to determine whether the iteration continues or not.
iter_con=true; % continues as default.
clear id_ex_self;
if num_matched > 0&&... % already have cloud shadow previously
(record_base_h_near > 0 && base_h >= record_base_h_near) % or more than the predicted cloud height.
iter_con=false;
end
clear pt_unsure;
% check the matched cloud shadow or not?
% the following rules are used to decide to continue or not.
if iter_con
if (thresh_match >= Tbuffer*record_thresh)&&...
(base_h < Max_cl_height-step_interval)&&...
(record_thresh < max_similar)
if thresh_match > record_thresh
% record max similarity and the corresponding cloud base height.
record_thresh=thresh_match;
% record_h=h;
record_base_h=base_h;
end
continue;
else
if (record_thresh >= Tsimilar)
% successfully find a cloud shadow
num_matched=num_matched+1; % indicates one more cloud shadow was found out.
% only when expected height available. (record_base_h_near>0)
if base_h<record_base_h_near
% but allow the searching reach to the neighboring clouds' height
if thresh_match>=record_thresh||thresh_match>=max_similar
record_thresh=thresh_match;
% record_h=h;
record_base_h=base_h;
end
continue; % much reach the predicted cloud height.
end
else
record_thresh=0;
continue;
end
end
end
% 1: continues; 0: not continue and get a cloud shadow
if num_matched<1
break;
end
if r_obj>num_pix&&...
cloud_type_cur<=num % cannot re-add for the first 14 clouds
matched_clds_centroid=[matched_clds_centroid;center_cur];
match_clds(cloud_type)=1;
height_clds_recorder=[height_clds_recorder;record_base_h];
% height_clds_recorder(cloud_type)=record_base_h;
record_base_h_num=record_base_h_num+1;
end
similar_num(cloud_type)=record_thresh;
if isequal(data_meta.Sensor,'S_MSI')
record_h = record_base_h;
h_bias=record_h-base_heigh_cloud;% hc-Ec
[tmp_xys_all(:,1),tmp_xys_all(:,2)]= getRealCloudPositionS2(orin_xys_all(:,1),...
orin_xys_all(:,2),h_bias,VZAxy,VAAxy,data_meta.Resolution);
elseif isequal(data_meta.Sensor,'L_OLI_TIRS')||...
isequal(data_meta.Sensor,'L_ETM_PLUS')||...
isequal(data_meta.Sensor,'L_TM')
record_h = double(10*(t_obj-temp_obj_all)/rate_elapse+record_base_h);
h_bias=record_h-base_heigh_cloud;% hc-Ec
sensor_heigh_bias=base_heigh_cloud+dem_base_heigh;
[tmp_xys_all(:,1),tmp_xys_all(:,2)]=getRealCloudPosition(orin_xys_all(:,1),...
orin_xys_all(:,2),h_bias,A,B,C,omiga_par,omiga_per,sensor_heigh_bias);
else
error('Only Landsats 4-7, Landsat 8 and Sentinel 2 data can be supported./n');
end
clear orin_xys_all;
i_vir=record_h/(sub_size*tan(sun_elevation_rad));
tmp_XY_type_all(:,2)=round(tmp_xys_all(:,1)-i_vir*cos(sun_tazi_rad)); % X is for col j,2
tmp_XY_type_all(:,1)=round(tmp_xys_all(:,2)-i_vir*sin(sun_tazi_rad)); % Y is for row i,1
clear tmp_xys_all i_vir;
tmp_scol_plane=tmp_XY_type_all(:,2);
tmp_srow_plane=tmp_XY_type_all(:,1);
clear tmp_XY_type_all;
tmp_tmp_i_plane_expd=tmp_srow_plane+dim_expd;
tmp_tmp_j_plane_expd=tmp_scol_plane+dim_expd;
clear tmp_srow_plane tmp_scol_plane;
avail_pixels=find(tmp_tmp_i_plane_expd>0&tmp_tmp_j_plane_expd>0&...
tmp_tmp_i_plane_expd<dim_expand(1)&tmp_tmp_j_plane_expd<dim_expand(2));
tmp_tmp_i_plane_expd=tmp_tmp_i_plane_expd(avail_pixels);
tmp_tmp_j_plane_expd=tmp_tmp_j_plane_expd(avail_pixels);
clear avail_pixels;
% matched shadow locations at plane.
tmp_tmp_id_plane_expd=sub2ind(dim_expand,tmp_tmp_i_plane_expd,tmp_tmp_j_plane_expd);
clear tmp_tmp_i_plane_expd tmp_tmp_j_plane_expd;
% matched shadow locations at real image (DEM surface).
tmp_srow=recorderRow(tmp_tmp_id_plane_expd);
tmp_scol=recorderCol(tmp_tmp_id_plane_expd);
clear tmp_tmp_id_plane_expd;
% remove the pixels out of box.
out_ids=tmp_srow<1|tmp_scol<1|...
tmp_srow>win_height|tmp_scol>win_width;
tmp_srow(out_ids)=[];
tmp_scol(out_ids)=[];
clear out_ids;
tmp_sid=sub2ind(dim,tmp_srow,tmp_scol);
clear tmp_srow tmp_scol;
% give shadow_cal=1
% data_shadow_matched(tmp_sid)=1;
if cloud_type_cur>num % re-visit the first 14 clouds.
% remove the matched before.
data_shadow_matched((data_shadow_matched==cloud_type))=0;
% and give new cloud shadow to this.
end
data_shadow_matched(tmp_sid)=cloud_type;
clear tmp_sid;
clear center_cur;
break;
end
end
data_cloud_matched=data_cloud_potential;
data_shadow_matched=uint8(data_shadow_matched>0);
% remove the cloud.
data_shadow_matched(data_cloud_matched==1)=0;
end
end