Spatial_Correlation_Function.py 文件源码

def cross_corr(img1,img2,mask=None):
    '''Compute the autocorrelation of two images.
        Right now does not take mask into account.
        todo: take mask into account (requires extra calculations)
        input: 
            img1: first image
            img2: second image
            mask: a mask array
        output:
            the autocorrelation of the two images (same shape as the correlated images)

    '''
    #if(mask is not None):
    #   img1 *= mask
    #  img2 *= mask

    #img1_mean = np.mean( img1.flat )
    #img2_mean = np.mean( img2.flat )

    # imgc = fftshift( ifft2(     
    #        fft2(img1/img1_mean -1.0 )*np.conj(fft2( img2/img2_mean -1.0 ))).real )

    #imgc = fftshift( ifft2(     
    #        fft2(  img1/img1_mean  )*np.conj(fft2(  img2/img2_mean   ))).real )

    imgc = fftshift( ifft2(     
            fft2(  img1  )*np.conj(fft2(  img2  ))).real )

    #imgc /= (img1.shape[0]*img1.shape[1])**2
    if(mask is not None):
        maskc = cross_corr(mask,mask)        
        imgc /= np.maximum( 1, maskc )


    return imgc