Specifications

MATLAB supports standard data and image
formats, including JPEG, TIFF, PNG, HDF,
HDF-EOS, FITS, Microsoft Excel, ASCII, and
binary files. It also supports multiband image
formats, such as LANDSAT. Low-level I/O
functions enable you to develop custom rou-
tines for working with any data format.
For medical imaging, the Image Processing
Toolbox supports the DICOM file format.
You can read and write DICOM images and
associated metadata and create custom data
dictionaries in MATLAB.
Pre- and Post-Processing Images
The Image Processing Toolbox provides
reference-standard algorithms for pre- and
post-processing tasks that solve frequent
system problems, such as interfering noise,
low dynamic range, out-of-focus optics,
and the difference in color representation
between input and output devices.
Enhancing Images
Image enhancement techniques in the Image
Processing Toolbox enable you to increase the
signal-to-noise ratio and accentuate image
features by modifying the colors or intensities
of an image. You can:
•
Perform histogram equalization
•
Perform decorrelation stretching
•
Remap the dynamic range
•
Adjust the gamma value
•
Perform linear, median, or adaptive filtering
The toolbox includes specialized filtering
routines and a generalized multidimensional
filtering function that handles integer image
types, multiple boundary padding options, and
convolution and correlation. Predefined filters
and functions for designing and implementing
your own linear filters are also provided.
your own linear filters are also provided.
SURFACE IMAGE
Atomic force microscope image of quantum semi-
conductor dots formed during the deposition of
indium arsenide onto gallium arsenide (left) and
the image segmented using the watershed trans-
form in the Image Processing Toolbox (right).
WATERSHED SEGMENTED IMAGE
Image courtesy of Ian Farrer, University of Cambridge.
Original image of rice grains with
nonuniform background intensity.
Result of subtraction of
nonuniformity from original.
Histogram plot of resultant image
with automatic thresholding.
A typical interactive
session using MATLAB
and the Image
Processing Toolbox to
perform connected com-
ponents analysis on an
image with nonuniform
background intensity.
Binary thresholded image.
Extraction of nonuniform background
intensity using morphological opening.
Measuring region properties, such as
the eccentricity of the rice grains.