1
44
F. Bayrak c¸ eken et al. / Spectrochimica Acta Part A 65 (2006) 143–146
high-resolution digital images. One way to quantify the ability
to resolve two level visual stimuli which are the same except
for their intensities or luminances is by measuring the just-
noticeable difference or short intensity discrimination. If the
observer is assumed to spend some time before making a deci-
sion, the result is obtained when the observer is adapted to
the intensity level. When the intensity level the observer is
adapted to is of a different form, the observer’s intensity res-
olution ability decreases. From this fact, if an image with a
large dynamic range is recorded on a medium with a small
dynamic range, such as film or paper, the contrast and there-
fore the details of the image are reduced, particularly in the very
bright and dark regions. In fact, the details of small variations
on the original analog spectral image can be re-emphasized by
using digital image processing techniques in which an image is
digitally formed. On the other hand, increasing the local con-
trast and reducing the overall dynamic range can significantly
enhance the quality of such an image. With this aim, such image
enhancement algorithms are required for images after digitiza-
tion process. In image enhancement, the main objective is to
make the processed image better in some sense than the unpro-
cessedimage. Inthiscase, theidealimagedependsonthecontext
of the problem and is often not well defined. In that sense, an
image is enhanced by modifying its contrast and/or dynamic
range. Improved image maps, more information and less noise
from the raw data onto the actual image further increase their
resolution. On the other side, in some cases, the measure-
ment results extracted from the experimental data might include
some measurement noises because of the insufficient number
of samples. This type of noise can be eliminated by apply-
ing digital filtering techniques like smoothing and averaging
Fig. 1. Flash photolysis of 3-methylbut-1-ene (3.4 Torr) + N2 (700 Torr) show-
ing the spectrum of ␣-methallyl radical and its decay, flash energy was 1125 J
(
original spectrum is taken by the permission of F. Bayrak c¸ eken).
The image of the original multi-resolution ␣-methallyl spec-
tra having 10 time intervals and five main absorption bands
recorded from the measurements (Fig. 1) was also examined
by using image analysis techniques in order to obtain the exact
absorption band places from the spectra. For that reason the
original spectral image was transformed to a gray level image
as,
y(i, j) = Gray-level{I(i, j)}
(1)
where I and y are the original spectral images and the resulting
256 gray-level image, respectively. The intensity levels of the
spectral image was normalized by using MATLAB functions in
order to reduce the computational costs as follows:
[
7].
y(i, j)
2
. Experimental
yn(i, j) =
(2)
{
y(i, j)}max
The flash photolysis apparatus consisted of two parallel pho-
where yn is the normalized image. Each horizontal time interval
from “before” to “after” in Fig. 1 were marked and separated
from the original spectral image to define the region of interest
totubes arranged in series, contained in a reflector, which was
flushed with oxygen-free nitrogen. The photoflash energies used
were 780–1125 J, and the flash duration was 4 s. All quartz
components were of spectrosilica grade. Spectra were recorded
on Hilger medium quartz instrument using Ilford-XK fast blue
sensitive plates sensitized with sodium salicylate. The plates
were photometered on a Joyce-Loebel recording microdensito-
meter with step wedge calibration. All the chemicals used were
spectroscopically pure. All kinetic spectroscopy was carried out
for single flashes giving <1% decomposition, as multiple flashes
resulted in the appearance of a continuous absorption spectrum
in the wavelength region of the methyl radical. Low pressures
of parent molecules were flashed after mixing with excess of
nitrogen to maintain isothermal conditions, pressures were mea-
sured with a McLeod gauge (up to 0.1 Torr), a spiral gauge
(
ROI) being analysed as follows:
yb(i, k) = y(i, j), k ∈ ROIb, b = 1, 2, . . . , 10
where y ’s show the blocks to be tried. Each time interval
cropped, as in Eq. (3), was defined as a one-dimensional density
row vector x(n) by computing the averages through the columns
(3)
b
of the matrix y (for each vertical axes) as,
b
M
ꢀ
1
x(n) =
yb(i, n)
(4)
M
i=1
Each element of the vector x(n) defines a distinct wavelength
and the amplitude value of that element gives its optical den-
sity in the spectral image. The elements of the vector x(n) were
smoothened by curve fitting in order to avoid noise effects and
obtain a better visual graphical representation for all absorption
bands than the original. Each band was identified from den-
sity information and plotted again as shown in Fig. 2, which is
an example of the separated band for 20 s measurement. The
(
0.1–50 Torr), and above 50 Torr, with a mercury manometer.
Products and residual parent molecules were dissolved in sev-
eral alcohols and the resulting solution concentrated to 20 l. A
sample of 4 l was used for analysis with a Griffin and George-
D6 gas chromatograph with a 12% polyethylene glycol column
◦
at 200 C.