In: Paparoditis N., Pierrot-Deseilligny M. Mallet C.. Tournaire O. (Eds). 1APRS. Vol. XXXVIII. Part ЗА - Saint-Mandé, France. September 1-3. 2010
MOTION BLUR DETECTION IN AERIAL IMAGES SHOT
WITH CHANNEL-DEPENDENT EXPOSURE TIME
L. Lelégard 0 ’*, M. Brédif 0 , B. Vallet 0 . D. Boldo b
a Université Paris Est, IGN, Laboratoire MATIS, 73 avenue de Paris, 94165 Saint-Mandé, France
(laman.lelegard, mathieu.bredif, bruno.vallet)@.ign.fr
b EDF R&D - Département STEP, 6 quai Watier, 78401 Chatou, France - didier.boldo@edf.fr
Commission III
KEY WORDS: Motion blur, blur detection, airborne imagery, Fourier Transform
ABSTRACT:
This paper presents a simple yet efficient approach for automatic blur detection in aerial images provided by a multi-channel digital
camera system. The blur in consideration is due to the airplane motion and causes anisotropy in the Fourier Transform of the image.
This anisotropy can be detected and estimated to recover the characteristics of the motion blur, but one cannot disambiguate the
anisotropy produced by a motion blur from the possible spectral anisotropy of the underlying sharp image. The proposed approach
uses a camera with channel-dependent exposure times to address this issue. Under this multi-exposure setting, the motion blur kernel
is scaled proportionally to the exposure-time, whereas the phase differences between the underlying sharp colour channels are
assumedly negligible. We show that considering the phase of the ratio of the Fourier Transforms of two channels enhances blur
detection. Results obtained on 2000 images confirm the operational efficiency of our method.
1. INTRODUCTION
For more than fifteen years, mapping agencies and photo-
grammetric companies have been working on digital airborne
image acquisition, phasing out traditional silver film. This
important change brought many improvements, especially in the
radiometric quality of images where each pixel could be given a
physical value after a radiometric calibration of the camera,
which was not the case with silver film. The chemical process of
film development cannot be entirely under control. A good
radiometric quality is often required in order to produce ortho
images (i.e. mosaics of images that can be geometrically
superposed with a map) without visible boundaries (Kasser &
Egels, 2002).
To provide high quality images, the flights often take place in
summer, when the brightness is optimal. However flying in
summer has one drawback: the significant tree foliage causes
problematic occlusions when studying the characteristics of the
ground level (topography, path, rivers, etc.). The only way to
have leafless trees is to fly the mission between autumn and
spring when the luminosity is weak. Thus, the exposure time
should be increased, at the risk of causing motion blur.
Fortunately, the images in which the blur is significant (more
than 2 pixels) represent a very small proportion of the mission.
In preparation for photogrammetric and remote sensing studies,
aerial acquisitions are planned with an important overlap
between two images. The strong overlaps generally chosen
ensure that a ground point appears on at least four pictures. This
redundancy is the reason why it can be chosen to simply remove
blurred images without trying any restoration. This choice is
justified by the fact that it is almost impossible to have all the
images seeing the same ground point blurred. Until now the
removal of blurred images was done manually by an operator.
We propose in this article an automatic method for blur
detection that makes this long and tedious work easier.
First, we will describe the channel-dependent exposure time
camera for which our method is designed. Then we will review
the state of the art, which will show that blur detection is less
discussed than blur correction. Our method of blur detection
will then be presented in two parts: first, a simple and mono
channel approach based on the module of the Fourier Transform
of the image, then an improvement based on a multi-channel
approach. A test on 2000 images eventually illustrates the
reliability of the method.
2. DATA ACQUISITION
The images are provided by a multi-channel camera system
(Figure 1). This multi-sensor system has been preferred to a
classical Bayer sensor for many reasons. Among them, the lack
of coloured artefacts, a better dynamic range in the shadowed
areas and the possibility of using a fourth channel in the near
infra-red wavelengths for remote sensing applications. In our
study, only the visible wavelengths (between 380 and 780 nm)
are considered.
The relative response of the three channels (R, G, B) are
influenced by the KAF-16801LE sensor performances (Eastman
Kodak Company, 2002) and by the colour filter transmission
(CAMNU, 2005) as illustrated on Figure 2. In particular, the
response in the blue channel is very low relative to other
channels. There are two solutions to deal with this problem. The
first idea is to simply multiply the blue signal by a constant to
enhance the blue channel, but its noise will be multiplied
Corresponding author.
