diff --git a/src/Images.jl b/src/Images.jl
index 413454b9..cd0ed111 100644
--- a/src/Images.jl
+++ b/src/Images.jl
@@ -46,6 +46,7 @@ include("labeledarrays.jl")
 include("algorithms.jl")
 include("connected.jl")
 include("edge.jl")
+include("dftRegistration.jl")
 
 __init__() = LibMagick.init()
 
@@ -249,7 +250,13 @@ export # types
     thin_edges_nonmaxsup_subpix,
 
     # phantoms
-    shepp_logan
+    shepp_logan,
+
+    # DFT registration
+    dftReg,
+    alignFromDft,
+    subpixelshift
+
 
 export # Deprecated exports
     ClipMin,
diff --git a/src/dftRegistration.jl b/src/dftRegistration.jl
new file mode 100644
index 00000000..66db7b71
--- /dev/null
+++ b/src/dftRegistration.jl
@@ -0,0 +1,172 @@
+### DFT registration
+## Algorithm from (and code very inspired by the matlab code provided by the authors):
+## Manuel Guizar-Sicairos, Samuel T. Thurman, and James R. Fienup, 
+##  "Efficient subpixel image registration algorithms," Opt. Lett. 33, 156-158 (2008).
+
+### Apply dft registration to an image/array (or each frame of such an image if the input is 3D) compared to a reference image (by default the first image of the image stack inputed). If align==false, returns an array with one row per frame in the image, and columns corresponding to the error, the phase difference, the estimated row shift and the estimated column shift. Otherwise returns the registered image.
+function dftReg(imgser;ref::AbstractArray=imgser[:,:,1],ufac::Int64=10,align::Bool=false)
+    ref = fft(ref)
+    imgF = fft(imgser,(1,2))
+    if ndims(imgF) == 2
+        results = dftRegfft(data(ref),imgF,ufac).'
+    else
+        results = zeros(size(imgF)[3],4)
+        for i=1:size(imgF)[3]
+           results[i,:] = dftRegfft(data(ref),imgF[:,:,i],ufac)
+        end
+    end
+    if align
+        return(alignFromDft(imgser,results))
+    else
+        return(results)
+    end
+end
+    
+
+### Align an image using the results of the dftReg function.
+function alignFromDft(img2reg::AbstractArray,dftRegRes)
+    imRes = similar(img2reg,Float64)
+    img2regF = fft(img2reg,(1,2))
+    if ndims(img2reg)==2
+        return(subpixelshift(img2regF,dftRegRes[2],dftRegRes[3]))
+    end
+    for i=1:size(dftRegRes)[1]
+        imRes[:,:,i] = subpixelshift(img2regF[:,:,i],dftRegRes[i,2],dftRegRes[i,3])
+    end
+    imRes
+end
+
+
+### The DFT algorithm : computes misalignment error, phase difference and row and column shifts between two images. The input is the fft transform of the two images, and the oversampling factor usfac.
+function dftRegfft(reffft,imgfft,usfac)
+    if usfac==0
+        ## Compute error for no pixel shift
+        CCmax = sum(reffft.*conj(imgfft))
+        rfzero = sumabs2(reffft)
+        rgzero = sumabs2(imgfft)
+        error = sqrt(abs(1 - CCmax*conj(CCmax)/(rgzero*rfzero)))
+        output = error
+    elseif usfac==1
+        ## Whole-pixel shift - Compute crosscorrelation by an IFFT and locate the peak
+        L = length(reffft)
+        CC = fftshift(reffft).*conj(fftshift(imgfft))
+        CC = ifft(ifftshift(CC))
+        loc = indmax(abs(CC))
+        CCmax=CC[loc]
+        rfzero = sumabs2(reffft)/L
+        rgzero = sumabs2(imgfft)/L
+        error = sqrt(abs(1 - CCmax*conj(CCmax)/(rgzero*rfzero)))
+
+        (m,n) = size(reffft)
+        md2 = div(m,2)
+        nd2 = div(n,2)
+        locI = ind2sub((m,n),loc)
+        
+        if locI[1]>md2
+            rowShift = locI[1]-m-1
+        else rowShift = locI[1]-1
+        end
+        if locI[2]>nd2
+            colShift = locI[2]-n-1
+            else colShift = locI[2]-1
+        end
+        output = [error,rowShift,colShift]
+    else
+        ## Partial pixel shift
+        
+        ##First upsample by a factor of 2 to obtain initial estimate
+        ##Embed Fourier data in a 2x larger array
+        dimR = size(reffft)
+        dimRL = map((x) -> x*2, dimR)
+        CC = zeros(Complex,dimRL)
+        CC[(dimR[1]+1-div(dimR[1],2)):(dimR[1]+1+div((dimR[1]-1),2)),(dimR[2]+1-div(dimR[2],2)):(dimR[2]+1+div((dimR[2]-1),2))] = fftshift(reffft).*conj(fftshift(imgfft))
+
+        ##  Compute crosscorrelation and locate the peak 
+        CC = ifft(ifftshift(CC))
+        loc = indmax(abs(CC))
+        (m,n) = size(CC)
+        locI = ind2sub((m,n),loc)
+        CCmax = CC[loc]
+
+        ## Obtain shift in original pixel grid from the position of the crosscorrelation peak
+        md2 = div(m,2)
+        nd2 = div(n,2)
+          
+        if locI[1] > md2
+            rowShift = locI[1]-m-1
+        else rowShift = locI[1]-1
+        end
+        
+        if locI[2] > nd2
+            colShift = locI[2]-n-1
+        else colShift = locI[2]-1
+        end
+        rowShift = rowShift/2
+        colShift = colShift/2
+
+        ## If upsampling > 2, then refine estimate with matrix multiply DFT
+        if usfac > 2
+            ### DFT Computation ###
+            # Initial shift estimate in upsampled grid
+            rowShift = iround(rowShift*usfac)/usfac
+            colShift = iround(colShift*usfac)/usfac
+            dftShift = div(ceil(usfac*1.5),2) ## center of output array at dftshift+1
+            ## Matrix multiply DFT around the current shift estimate
+            CC = conj(dftups(imgfft.*conj(reffft),ceil(Int64,usfac*1.5),ceil(Int64,usfac*1.5),usfac,dftShift-rowShift*usfac,dftShift-colShift*usfac))/(md2*nd2*usfac^2)
+            ## Locate maximum and map back to original pixel grid
+            loc = indmax(abs(CC))
+            locI = ind2sub(size(CC),loc)
+            CCmax = CC[loc]
+            rgzero = dftups(reffft.*conj(reffft),1,1,usfac)[1]/(md2*nd2*usfac^2)
+            rfzero = dftups(imgfft.*conj(imgfft),1,1,usfac)[1]/(md2*nd2*usfac^2)
+            locI = map((x) -> x - dftShift - 1,locI)
+            rowShift = rowShift + locI[1]/usfac
+            colShift = colShift + locI[2]/usfac
+        else  
+            rgzero = sum(reffft.*conj(reffft))/m/n
+            rfzero = sum(imgfft.*conj(imgfft))/m/n  
+        end
+        error = sqrt(abs(1 - CCmax*conj(CCmax)/(rgzero*rfzero)))
+        ## If its only one row or column the shift along that dimension has no effect. We set to zero.
+        if md2 == 1
+            rowShift = 0
+        end
+        if  nd2==1
+            colShift = 0
+        end
+        output = [error,rowShift,colShift]
+    end
+    output
+end
+
+### Upsampled DFT by matrix multiplies, can compute an upsampled DFT in just a small region
+function dftups(inp,nor,noc,usfac=1,roff=0,coff=0)
+    (nr,nc) = size(inp)  
+    kernc = exp((-1im*2*pi/(nc*usfac))*((ifftshift(0:(nc-1)))-floor(nc/2))*((0:(noc-1))-coff).')
+    kernr = exp((-1im*2*pi/(nr*usfac))*((0:(nor-1))-roff)*(ifftshift(0:(nr-1))-floor(nr/2)).')
+    kernr*data(inp)*kernc
+end
+
+### Translate a 2D image/array at subpixel resolution. Outputs the original images translated. If the input is of complex type, it is assumed to be the Fourier transform of the image to shift.
+function subpixelshift(img::AbstractArray,rowShift,colShift)
+    img = fft(img)
+    (nr,nc) = size(img)
+    Nr = ifftshift((-div(nr,2)):(ceil(Int64,nr/2)-1))
+    Nc = ifftshift((-div(nc,2)):(ceil(Int64,nc/2)-1))
+    Greg = data(img).* exp(2im*pi*((-rowShift*Nr/nr).-(colShift*Nc/nc).'))
+    copyproperties(img,real(ifft(Greg)))
+end         
+
+function subpixelshift(img::AbstractArray{Complex{Float64},2},rowShift,colShift)
+    (nr,nc) = size(img)
+    Nr = ifftshift((-div(nr,2)):(ceil(Int64,nr/2)-1))
+    Nc = ifftshift((-div(nc,2)):(ceil(Int64,nc/2)-1))
+    Greg = data(img) .* exp(2im*pi*((-rowShift*Nr/nr).-(colShift*Nc/nc).'))
+    copyproperties(img,real(ifft(Greg)))
+end
+           
+
+
+
+
+