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Joint Demosaicing and Super-Resolution Imaging from a Set of Unregistered Aliased Images
 

Summary: Joint Demosaicing and Super-Resolution Imaging from a Set
of Unregistered Aliased Images
Patrick Vandewallea, Karim Krichanea, David Alleyssonb, and Sabine S¨usstrunka
aSchool of Computer and Communication Sciences, Ecole Polytechnique F´ed´erale de Lausanne
(EPFL), CH-1015 Lausanne, Switzerland;
bLaboratoire de Psychologie et Neurocognition, Universit´e Pierre-Mendes France (UPMF),
F-38041 Grenoble, France.
ABSTRACT
We present a new algorithm that performs demosaicing and super-resolution jointly from a set of raw images
sampled with a color filter array. Such a combined approach allows us to compute the alignment parameters
between the images on the raw camera data before interpolation artifacts are introduced. After image registration,
a high resolution color image is reconstructed at once using the full set of images. For this, we use normalized
convolution, an image interpolation method from a nonuniform set of samples. Our algorithm is tested and
compared to other approaches in simulations and practical experiments.
Keywords: Demosaicing, super-resolution, image registration, aliasing.
1. INTRODUCTION
The resolution of an image taken with a digital camera is mainly determined by its lens and its sensor. If the
modulation transfer function (MTF) of the lens removes too much of the high frequency scene information, the
image will be blurred and details cannot be distinguished. Similarly, if the sampling frequency at the sensor
(determined by the number of pixels and the sensor size) is lower than twice the maximum signal frequency

  

Source: Alleysson, David - Laboratoire de Psychologie et NeuroCognition, Université Pierre Mendes France

 

Collections: Biology and Medicine