Geophysical data acquisition, processing and interpretation - Geophysics for the Mineral Exploration Geoscientist - page 51

An almost in nite array of images can be created from a
single dataset. Furthermore, different filtered forms of the
same data, or even other types of data, can be integrated into
a single image to allowmore reliable analysis of the data. It is
clear from the various 2D displays shown in Fig. 2.30 that an
image allows easy recognition of regions having different
characteristics, and also linear features. These are funda-
mental to the interpretation of geophysical datasets, the
principal reason for their popularity. If actual amplitudes
are required, or gradients are important, then these can be
provided most effectively by plotting contours of amplitude
onto the pixel image: for examples see Figs. 2.12 , 3.15 , 3.21
and 3.70a . Numerous examples of pixel images of different
kinds of geophysical data are presented throughout the
following chapters. We describe the details of image process-
ing applied to the display of geophysical data in Section 2.8.2 .

emphasise particular features within in the data and create
a more easily interpretable product. It is distinct from data
enhancement where the emphasis is on numerical process-
ing to highlight particular characteristics of the data or to
improve the signal-to-noise ratio. Our description applies
equally to the voxel displays used to present data volumes.
At its most fundamental level, digital image processing
involves the representation of each grid (data) value as a
coloured pixel. The resultant image is known as a pseudo-
colour display, because the colours are not the true colours
of the parameter displayed. The physical size of each pixel
and the number of the pixels in the display depends on the
hardware used to display the image. Depending on the
resolution of the display device and the amount of data
to be displayed, each node in the data grid is assigned to a
pixel in the display. The amplitude of the data value is used
to control the colour of the pixel. This raises two funda-
mental issues: how the display colours are selected, and
how these colours are assigned to the (grid) data values.

2.8.1.2 3D display
When data are coordinated in a 3D space and are distrib-
uted throughout that space, they are referred to as 3D data,
and pseudovolumes, paravolumes or 3D models may be
created. They are usually presented with a voxel based
display. The need to integrate, display and analyse many
different types of 3D data in unison has led to the devel-
opment of computer-based 3D visualisation systems. Typ-
ically, 3D geophysical models, surface and downhole
petrophysical values and vector measurements can be inte-
grated and displayed with many other types of 3D data,
such as geochemical, geological, mining and geographical
information. Polzer ( 2007 ) demonstrates the application of
3D data visualisation in nickel exploration. These systems
allow the integrated 3D database to be rotated and viewed
from any direction, from within the ground or from above
it, and allow multiple views of the data simultaneously. In
addition, visual enhancements and

2.8.2.1 RGB colour model
The number of different colours available, and therefore the
ability to accurately represent the amplitude variations of the
data, depends on both hardware and software considerations.
Digital display devices use the primary colours of light:
red (R), green (G) and blue (B) ( Fig. 2.31a ) , which can be
mixed to create a pixel of any colour. For example, mixing
equal amounts of two of the primary colours creates the
secondary colours yellow, cyan and magenta. Every colour
is represented by its location in the RGB colour space
which can be visualised as a Cartesian coordinate system
( Fig 2.31b ). In Fig. 2.31b , black occurs at the origin (R ¼ 0,

G ¼ 0, B ¼ 0), with shades of grey and white plotting on the

' , along which all three primary colours

are mixed in equal amounts (R

grey ' or ' intensity axis '

B). White is produced by
mixing the maximum amounts of the three primaries.
Typically an eight-bit hardware architecture is used to
represent the amount of each primary colour in a three-
colour RGB display, so each primary colour has 2 8 (256)
discrete intensity levels (0 to 255) and each pixel carries 24
(3

¼ G ¼

filters can be applied to
any of the parameters contained in the database, such as
data-type, feature, text values, numerical values, voxels etc.,
and applied to the whole database or parts of it (for
example, selected by geological criteria). It is beyond our
scope to investigate further this developing area of infor-
mation technology; but it is likely that the use of 3D
visualisation systems for presenting and working with
multiple datasets will become the norm.

8) bits. By mixing the three colours, up to 256 3
(16,777,216 2 24 ) different colours can be speci ed,

referred to as 24-bit colour. Several techniques are used
for assigning colours to pixels.

¼

2.8.2 Image processing

Hue-saturation-intensity
Colours in the RGB colour space can also be de ned in
terms of hue (H),

We use the term image processing to mean enhancements
applied to pixel displays of gridded data, primarily to saturation (S)andinten ty I)