We
take
an input image and blur it using a yaw camera
motion. We solve
for the Motion
Density Function (MDF)
restricted to x-translation
with the latent image fixed to the known ground truth image.Finally,
we deblur
the image using the kernels generated by the MDF. We measure the PSNR
of the deblurred image w.r.t. the ground truth. A higher PSNR indicates
that x-translation performed
a good approximation of the yaw
motion.
Following is a plot of the PSNR as we vary the focal length. We
decreased the yaw motion
with the increasing focal length to keep the kernel size similar across
all tests. This is to avoid confounding the PSNR metric by the
non-blind deconvolution errors resulting from different kernel sizes.
The PSNR improvement levels out quickly and the translation-only
kernels start to
approximate the yaw
kernels
quite well. Hence this approximation holds well for not-very short
focal lengths.
Notice the image corners where translation-only
model has problems.
Focal-length
Blurred
Image
Deblurred
Image
Actual
blur kernels
Recovered
blur kernels using
ground truth image as initialization