A computer-implemented method of structural masking for progressive health monitoring of a structural component, comprising: receiving a current image of the structural component; aligning, by a processor, the current image and a reference image of the structural component; performing, by the processor, a structure estimation on the current image and the reference image to produce a current structure estimate image and a reference structure estimate image; generating, by the processor, a structural mask from the reference structure estimate image; masking, by the processor, the current structure estimate image with the structural mask to identify one or more health monitoring analysis regions comprising a potential defect or damaged area appearing in the masked current structure estimate image that does not appear in the reference structure estimate image; characterized in that the structural masking focuses on unusual structures in the current image by ignoring expected structures from the reference image; wherein the generation of the structural mask is obtained by dilation of the reference structure estimate image, wherein dilation of the reference structure estimate image widens edges to include neighborhood regions in the structural mask; wherein progressive crack detection is applied to multiple images of the structural component after structural masking is applied to the images by performing additional steps comprising: detecting a plurality of points in the images after the structural masking; performing line segment formation by tracking the points; and estimating line segment growth with respect to time between a plurality of the images. receiving a current image of the structural component; aligning, by a processor, the current image and a reference image of the structural component; performing, by the processor, a structure estimation on the current image and the reference image to produce a current structure estimate image and a reference structure estimate image; generating, by the processor, a structural mask from the reference structure estimate image; masking, by the processor, the current structure estimate image with the structural mask to identify one or more health monitoring analysis regions comprising a potential defect or damaged area appearing in the masked current structure estimate image that does not appear in the reference structure estimate image; characterized in that the structural masking focuses on unusual structures in the current image by ignoring expected structures from the reference image; wherein the generation of the structural mask is obtained by dilation of the reference structure estimate image, wherein dilation of the reference structure estimate image widens edges to include neighborhood regions in the structural mask; wherein progressive crack detection is applied to multiple images of the structural component after structural masking is applied to the images by performing additional steps comprising: detecting a plurality of points in the images after the structural masking; performing line segment formation by tracking the points; and estimating line segment growth with respect to time between a plurality of the images. detecting a plurality of points in the images after the structural masking; performing line segment formation by tracking the points; and estimating line segment growth with respect to time between a plurality of the images.