Proposed BSc/MSc
Project for AY 2005-2006
Moments based super-resolution shape reconstruction algorithms for photogrammetry
Keywords: Photogrammetry, Object (Shape) determination from
moments, Sampling signals with Finite Rate of
Innovation (FRI), Complex-moments, Annihilating filter methods.
Required skills: Basic knowledge of signal processing, interest (and
aptitude) towards GUI development in Matlab (or C++ or Java).
Number of students: One.
Secondary support: Mr Pancham Shukla (RA and PhD student of Dr P L Dragotti)
Room 808, http://www.commsp.ee.ic.ac.uk/~pancham/index.html
Abstract: Photogrammetry (or remote sensing) is the
technique of measuring 2-D (or 3-D) objects (or their coordinates) from
photographs, or from the imagery stored on electronic media through CCD cameras or radiation sensors such as optical or
microwave scanners. Its most important feature is the fact that the objects are
measured without
being touched. Photogrammetry has
many applications such as determining crop yield, illegal intrusion in vast
land fields, military and defence surveillance, in geophysics, and in robot
vision. Additionally, in many situations, these applications can be processed
in such a way that the resultant imagery can be modelled with piecewise polynomial
approximations.
In practice, due to hardware of the CCD
camera (lenses), and in order to obtain efficient data storage, the obtained
image is a prefilterd and sampled version (blurred
and lower resolution) of the original (analogue) non-bandlimited scene. Hence
it is not possible to precisely determine (reconstruct) desired 2-D shapes from
that blurred (or sampled) version by applying
In this project, student will gain the understanding of
recently developed sampling theories (FRI sampling), fundamental aspects of
digital imaging, photogrammetry, various types of
moments (geometric and complex) and their signal/image processing applications
in determining image shapes. Student will start with estimation of simple
shapes such as polygons, circles, and ellipses, and thereafter other smooth
objects with unknown boundaries. The student is expected to understand and
verify the existing algorithms, and contribute in optimising these algorithms
by extracting minimum possible coordinates to represent such shapes from their
finite moments. Finally, the student is expected to develop a professional
looking photogrammetry GUI for visualization of the
results in Matlab (or C++ or Java) for phantom images and simple real images.