📄 readme.txt
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This program contains the image reconstruction algorithms.
Following is a listing of the functions required to implement the algorithms.
It is assumed that the user has available the following matlab toolboxes:
Optimization Toolbox
Signal Processing Toolbox
Statistic Toolbox
Image Processing Toolbox
GENERATION OF SIMULATED DATA
Samples.m
Graphical user interface (GUI) to visualize the estimated sample locations
using points.m function.
points.m
Generates the sample position matrix.
echoback.m
Generate the target echo signature.
echobackcall.m
Loads data and provides point position in the target.
IMAGE RECONSTRUCTION FUNCTIONS
final.m
Calls one of the several interpolation functions.
threest.m
Three step interpolation function. It implements the three steps of the
one-dimensional interpolation methods. It must call one of the functions
among normal_l.m, normal_c.m or sinky.m.
normal_l.m
Linear interpolation function.
normal_c.m
Cubic splines interpolation function.
sinky.m
Shannon reconstruction function.
nene.m
Nearest neighbor approximation function
euclide.m
Euclidean approximation function.
fsoum1.m
Airy pattern interpolation function.
fsoum2.m
Spatial domain interpolation function.
IMAGING PROGRAMS
soplot.m
Plots original images and interpolated images.
somax.m
Creates a GUI to find the amplitude of a local maxima.
ALGORITHM IMPLEMENTATION
1. Generate the estimated sample locations using samples.m
2. Generate the target echo signature with echobackcall.m if a simulated target
is desired. Skip this step if real data is available. If real data is
used, then the real data must be saved with zdata.mat.
3. Interpolate the data using final.m, which calls one of several interpolation
functions. Note that threest.m calls one of three one-dimensional
interpolation functions.
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