Index: /trunk/src/get_field.m =================================================================== --- /trunk/src/get_field.m (revision 878) +++ /trunk/src/get_field.m (revision 879) @@ -788,5 +788,5 @@ set(handles.Coord_x,'Value',coord_val(1)) set(handles.Coord_y,'Value',coord_val(2)) - if numel(ListCoord)>=3 + if numel(coord_val)>=3 set(handles.Coord_z,'Value',coord_val(3)) end Index: /trunk/src/series/civ_series.m =================================================================== --- /trunk/src/series/civ_series.m (revision 878) +++ /trunk/src/series/civ_series.m (revision 879) @@ -958,5 +958,5 @@ MinA=min(min(par_civ.ImageA)); %MinB=min(min(par_civ.ImageB)); -check_undefined=false(size(par_civ.ImageA)); +%check_undefined=false(size(par_civ.ImageA)); if isfield(par_civ,'Mask') && ~isempty(par_civ.Mask) checkmask=1; @@ -990,6 +990,4 @@ image1_crop=MinA*ones(numel(subrange1_y),numel(subrange1_x));% default value=min of image A image2_crop=MinA*ones(numel(subrange2_y),numel(subrange2_x));% default value=min of image A - mask1_crop=ones(numel(subrange1_y),numel(subrange1_x));% default value=1 for mask - mask2_crop=ones(numel(subrange2_y),numel(subrange2_x));% default value=1 for mask check1_x=subrange1_x>=1 & subrange1_x<=par_civ.ImageWidth;% check which points in the subimage 1 are contained in the initial image 1 check1_y=subrange1_y>=1 & subrange1_y<=par_civ.ImageHeight; @@ -998,26 +996,39 @@ image1_crop(check1_y,check1_x)=par_civ.ImageA(subrange1_y(check1_y),subrange1_x(check1_x));%extract a subimage (correlation box) from image A image2_crop(check2_y,check2_x)=par_civ.ImageB(subrange2_y(check2_y),subrange2_x(check2_x));%extract a larger subimage (search box) from image B - mask1_crop(check1_y,check1_x)=check_undefined(subrange1_y(check1_y),subrange1_x(check1_x));%extract a mask subimage (correlation box) from image A - mask2_crop(check2_y,check2_x)=check_undefined(subrange2_y(check2_y),subrange2_x(check2_x));%extract a mask subimage (search box) from image B - sizemask=sum(sum(mask1_crop))/(numel(subrange1_y)*numel(subrange1_x));%size of the masked part relative to the correlation sub-image - if sizemask > 1/2% eliminate point if more than half of the correlation box is masked - F(ivec)=3; % + if checkmask + mask1_crop=ones(numel(subrange1_y),numel(subrange1_x));% default value=1 for mask + mask2_crop=ones(numel(subrange2_y),numel(subrange2_x));% default value=1 for mask + mask1_crop(check1_y,check1_x)=check_undefined(subrange1_y(check1_y),subrange1_x(check1_x));%extract a mask subimage (correlation box) from image A + mask2_crop(check2_y,check2_x)=check_undefined(subrange2_y(check2_y),subrange2_x(check2_x));%extract a mask subimage (search box) from image B + sizemask=sum(sum(mask1_crop))/(numel(subrange1_y)*numel(subrange1_x));%size of the masked part relative to the correlation sub-image + if sizemask > 1/2% eliminate point if more than half of the correlation box is masked + F(ivec)=3; % + else + image1_crop=image1_crop.*~mask1_crop;% put to zero the masked pixels (mask1_crop='true'=1) + image2_crop=image2_crop.*~mask2_crop; + image1_mean=mean(mean(image1_crop))/(1-sizemask); + image2_mean=mean(mean(image2_crop))/(1-sizemask); + end else - image1_crop=image1_crop.*~mask1_crop;% put to zero the masked pixels (mask1_crop='true'=1) - image2_crop=image2_crop.*~mask2_crop; - image1_mean=mean(mean(image1_crop))/(1-sizemask); - image2_mean=mean(mean(image2_crop))/(1-sizemask); - %threshold on image minimum - if check_MinIma && (image1_mean < par_civ.MinIma || image2_mean < par_civ.MinIma) - F(ivec)=3; - end - %threshold on image maximum - if check_MaxIma && (image1_mean > par_civ.MaxIma || image2_mean > par_civ.MaxIma) - F(ivec)=3; - end - end + image1_mean=mean(mean(image1_crop)); + image2_mean=mean(mean(image2_crop)); + end + %threshold on image minimum + if check_MinIma && (image1_mean < par_civ.MinIma || image2_mean < par_civ.MinIma) + F(ivec)=3; + end + %threshold on image maximum + if check_MaxIma && (image1_mean > par_civ.MaxIma || image2_mean > par_civ.MaxIma) + F(ivec)=3; + end + if F(ivec)~=3 - image1_crop=(image1_crop-image1_mean).*~mask1_crop;%substract the mean, put to zero the masked parts - image2_crop=(image2_crop-image2_mean).*~mask2_crop; + if checkmask + image1_crop=(image1_crop-image1_mean).*~mask1_crop;%substract the mean, put to zero the masked parts + image2_crop=(image2_crop-image2_mean).*~mask2_crop; + else + image1_crop=(image1_crop-image1_mean); + image2_crop=(image2_crop-image2_mean); + end if CheckDeformation xi=(1:mesh:size(image1_crop,2)); Index: /trunk/src/series/stereo_civ.m =================================================================== --- /trunk/src/series/stereo_civ.m (revision 878) +++ /trunk/src/series/stereo_civ.m (revision 879) @@ -903,5 +903,5 @@ nbvec=size(par_civ.Grid,1); -%% prepare correlation and search boxes +%% prepare correlation and search boxes ibx2=floor(par_civ.CorrBoxSize(1)/2); iby2=floor(par_civ.CorrBoxSize(2)/2); @@ -945,23 +945,24 @@ %% Apply mask - % Convention for mask IDEAS TO IMPLEMENT ? - % mask >200 : velocity calculated - % 200 >=mask>150;velocity not calculated, interpolation allowed (bad spots) - % 150>=mask >100: velocity not calculated, nor interpolated - % 100>=mask> 20: velocity not calculated, impermeable (no flux through mask boundaries) - % 20>=mask: velocity=0 +% Convention for mask IDEAS TO IMPLEMENT ? +% mask >200 : velocity calculated +% 200 >=mask>150;velocity not calculated, interpolation allowed (bad spots) +% 150>=mask >100: velocity not calculated, nor interpolated +% 100>=mask> 20: velocity not calculated, impermeable (no flux through mask boundaries) +% 20>=mask: velocity=0 checkmask=0; MinA=min(min(par_civ.ImageA)); -MinB=min(min(par_civ.ImageB)); +%MinB=min(min(par_civ.ImageB)); +%check_undefined=false(size(par_civ.ImageA)); if isfield(par_civ,'Mask') && ~isempty(par_civ.Mask) - checkmask=1; - if ~isequal(size(par_civ.Mask),[npy_ima npx_ima]) + checkmask=1; + if ~isequal(size(par_civ.Mask),[npy_ima npx_ima]) errormsg='mask must be an image with the same size as the images'; return - end - % check_noflux=(par_civ.Mask<100) ;%TODO: to implement + end + % check_noflux=(par_civ.Mask<100) ;%TODO: to implement check_undefined=(par_civ.Mask<200 & par_civ.Mask>=20 ); -% par_civ.ImageA(check_undefined)=MinA;% put image A to zero (i.e. the min image value) in the undefined area -% par_civ.ImageB(check_undefined)=MinB;% put image B to zero (i.e. the min image value) in the undefined area + % par_civ.ImageA(check_undefined)=MinA;% put image A to zero (i.e. the min image value) in the undefined area + % par_civ.ImageB(check_undefined)=MinB;% put image B to zero (i.e. the min image value) in the undefined area end @@ -997,10 +998,11 @@ check1_y=subrange1_y>=1 & subrange1_y<=par_civ.ImageHeight; check2_x=subrange2_x>=1 & subrange2_x<=par_civ.ImageWidth;% check which points in the subimage 2 are contained in the initial image 2 - check2_y=subrange2_y>=1 & subrange2_y<=par_civ.ImageHeight; + check2_y=subrange2_y>=1 & subrange2_y<=par_civ.ImageHeight; image1_crop(check1_y,check1_x)=par_civ.ImageA(subrange1_y(check1_y),subrange1_x(check1_x));%extract a subimage (correlation box) from image A image2_crop(check2_y,check2_x)=par_civ.ImageB(subrange2_y(check2_y),subrange2_x(check2_x));%extract a larger subimage (search box) from image B - mask1_crop(check1_y,check1_x)=check_undefined(subrange1_y(check1_y),subrange1_x(check1_x));%extract a mask subimage (correlation box) from image A - mask2_crop(check2_y,check2_x)=check_undefined(subrange2_y(check2_y),subrange2_x(check2_x));%extract a mask subimage (search box) from imag - sizemask=sum(sum(mask1_crop))/(numel(subrange1_y)*numel(subrange1_x));%size of the masked part relative to the correlation sub-image + if checkmask + mask1_crop(check1_y,check1_x)=check_undefined(subrange1_y(check1_y),subrange1_x(check1_x));%extract a mask subimage (correlation box) from image A + mask2_crop(check2_y,check2_x)=check_undefined(subrange2_y(check2_y),subrange2_x(check2_x));%extract a mask subimage (search box) from imag + sizemask=sum(sum(mask1_crop))/(numel(subrange1_y)*numel(subrange1_x));%size of the masked part relative to the correlation sub-image if sizemask > 1/2% eliminate point if more than half of the correlation box is masked F(ivec)=3; % @@ -1010,6 +1012,9 @@ image1_mean=mean(mean(image1_crop))/(1-sizemask); image2_mean=mean(mean(image2_crop))/(1-sizemask); -% image1_mean=mean(mean(image1_crop)); -% image2_mean=mean(mean(image2_crop)); + end + else + image1_mean=mean(mean(image1_crop)); + image2_mean=mean(mean(image2_crop)); + end %threshold on image minimum if check_MinIma && (image1_mean < par_civ.MinIma || image2_mean < par_civ.MinIma) @@ -1020,20 +1025,23 @@ F(ivec)=3; end - end if F(ivec)~=3 - image1_crop=(image1_crop-image1_mean).*~mask1_crop;%substract the mean, put to zero the masked parts - image2_crop=(image2_crop-image2_mean).*~mask2_crop; + image1_crop=(image1_crop-image1_mean);%substract the mean, put to zero the masked parts + image2_crop=(image2_crop-image2_mean); + if checkmask + image1_crop=image1_crop.*~mask1_crop;% put to zero the masked parts + image2_crop=image2_crop.*~mask2_crop; + end if CheckDeformation - xi=(1:mesh:size(image1_crop,2)); - yi=(1:mesh:size(image1_crop,1))'; - [XI,YI]=meshgrid(xi-ceil(size(image1_crop,2)/2),yi-ceil(size(image1_crop,1)/2)); - XIant=XI-par_civ.DUDX(ivec)*XI-par_civ.DUDY(ivec)*YI+ceil(size(image1_crop,2)/2); - YIant=YI-par_civ.DVDX(ivec)*XI-par_civ.DVDY(ivec)*YI+ceil(size(image1_crop,1)/2); - image1_crop=interp2(image1_crop,XIant,YIant); - image1_crop(isnan(image1_crop))=0; - xi=(1:mesh:size(image2_crop,2)); - yi=(1:mesh:size(image2_crop,1))'; - image2_crop=interp2(image2_crop,xi,yi,'*spline'); - image2_crop(isnan(image2_crop))=0; + xi=(1:mesh:size(image1_crop,2)); + yi=(1:mesh:size(image1_crop,1))'; + [XI,YI]=meshgrid(xi-ceil(size(image1_crop,2)/2),yi-ceil(size(image1_crop,1)/2)); + XIant=XI-par_civ.DUDX(ivec)*XI-par_civ.DUDY(ivec)*YI+ceil(size(image1_crop,2)/2); + YIant=YI-par_civ.DVDX(ivec)*XI-par_civ.DVDY(ivec)*YI+ceil(size(image1_crop,1)/2); + image1_crop=interp2(image1_crop,XIant,YIant); + image1_crop(isnan(image1_crop))=0; + xi=(1:mesh:size(image2_crop,2)); + yi=(1:mesh:size(image2_crop,1))'; + image2_crop=interp2(image2_crop,xi,yi,'*spline'); + image2_crop(isnan(image2_crop))=0; end sum_square=(sum(sum(image1_crop.*image1_crop)));%+sum(sum(image2_crop.*image2_crop)))/2; @@ -1045,6 +1053,6 @@ [y,x] = find(result_conv==255,1); subimage2_crop=image2_crop(y:y+2*iby2/mesh,x:x+2*ibx2/mesh);%subimage of image 2 corresponding to the optimum displacement of first image - sum_square=sum_square*sum(sum(subimage2_crop.*subimage2_crop));% product of variances of image 1 and 2 - sum_square=sqrt(sum_square);% sqrt of the variance product to normalise correlation + sum_square=sum_square*sum(sum(subimage2_crop.*subimage2_crop));% product of variances of image 1 and 2 + sum_square=sqrt(sum_square);% sqrt of the variance product to normalise correlation if ~isempty(y) && ~isempty(x) try @@ -1055,8 +1063,8 @@ end - + utable(ivec)=vector(1)*mesh+shiftx(ivec); vtable(ivec)=vector(2)*mesh+shifty(ivec); - + xtable(ivec)=iref+utable(ivec)/2-0.5;% convec flow (velocity taken at the point middle from imgae 1 and 2)