This thesis examines the application of internal imaging technologies to the
detection of defects within felled logs. This application requires images of
moderate resolution to be generated at high-speeds. Transmission tomography
is suggested as the most appropriate imaging technology, with particular
reference to X-ray transmission tomography. High-speed X-ray scanners
suitable to the application exist.
An international literature search was performed to find reconstruction systems
capable of high-speed reconstruction of the X-ray data. Those systems
claiming to be high-speed are discussed in regard to their means of achieving
high-speed reconstruction. The discussions show that most effort has been
directed toward sophisticated hardware implementation of the reconstruction
process, rather then the mathematics of the reconstruction process itself. To
increase the achievable rate of reconstruction, the mathematics of each process
in the reconstruction algorithm are examined in this thesis, with the aim of
reducing computational complexity.
Convolution backprojection is the most commonly used reconstruction method
in transmission tomography when the X-ray data are complete, and can be
neatly separated into two separate processes, convolution (filtering) and
backprojection, as the name suggests. This reconstruction method was chosen
as suitable for the log processing application because of its mathematical
simplicity and quality of image reconstruction.
Truncation of the convolution kernel is examined, and simulated results show
adequate reconstruction quality with significant truncation. An inexpensive
hardware design capable of performing the convolution operation in real-time
The backprojection process normally employed is computationally expensive,
and is the major encumbrance to the realisation of simple high speed image
reconstruction from projections. A new backprojection algorithm for use in
high-speed parallel-ray tomographic reconstruction systems is presented. The
algorithm has the same functionality as the standard backprojection algorithm.
However it has been arranged so that fast table look-up methods may be used,
eliminating the need for time consuming mathematical calculations. The
modified backprojection algorithm reduces the size of the required look-up
table by an order of magnitude. Simulated results using the modified algorithm
are provided and compared to those obtained using the unmodified algorithm.
The resulting images are comparable with respect to feature identification,
confirming that the two algorithms function similarly. High-speed
implementations of the modified backprojection process used in tomographic
reconstruction are presented.
By combining both the convolution and backprojection implementations
presented, an inexpensive reconstruction system suitable for detection of
defects in felled logs is achievable.