DIP with Khoros 2: List of Experiments

Cies Island, Vigo, Spain

1. Data Model, Programming and Visualization Tools

1. Khoros 2: Data Model, Programming and Visualization Tools
   cantata, interactive and non-interactive plotting,
   interactive and non-interactive image display,
   image animate, geometry and volume

1. Image Representation
   pixel data types, header file information, image dimensions
   Data Object Info, 2D Plot, Display Image
2. Image Visualization
   header information, roi, zoom, intensity profile,
   print pixel values
   Data Object Info,
   Extract,2D Plot, 3D Plot, Display Image,
   Supported Formats, Expand
3. Image Statistics, Histogram
   statistics, histogram
   Statistics, Histogram, 2D Plot
4. Pixel Overflow
   adding byte-pixel to a constant
   Convert Type, Add
5. Data Type Conversion
   data type dependencies (color rendering), image display
   Convert Type (scaling, offset)

1. Generation of Trapezoidal Data
   ramp, piecewise linear, impulse
   Impulse, Piecewise Linear
2. Generation of Sinusoidal Data
   sinusoids
   Sinusoidal, Extract
3. Spatial Resolution/Image Composing I
   pixel resolution, world pixel dimension
   Extract, Inset, Resample
4. Contrast Phenomena/Image Composing II
   simultaneos contrast phenomena, human visual system
   Box Projection, Inset
5. Editing/Image Composing III
   extract, inset, flip and data reorientation operations
   Extract, Inset, Flip Object, Reorient Axes
6. RGB Color Model
   RGB color band decomposition
   Extract, Pad, Add
7. Translation, Rotation, Scaling/Geometric Transformations I
   scaling, translation and rotation
8. Checkerboard Effect/Geometric Transformation II
   image resolution, checkerboard effect
   Shrink, Expand
9. ASCII Data Processing
   spatial information vs. statistics, histogram
   Convert Type, Reorient, Supported Formats
   Import ASCII, Command Icon, Histogram
10. Labeling
    4 and 8 connectivity
    labeling, expand, autocolor
11. Area Distribution
    histogram of a histogram
    Labeling(MMACH), Histogram, Print Data

1. Patterns
   Impulse, Sinusoid, Clip Maximum, Extract,
   Inset, Expand, Translate
2. Image Combining
   combine image geometrically using a chessboard grid
   Gate Data, Impulse, Translate, Extract, Expand
3. Image Overlaying I
   overlay of a line grid on a zoomed image
   Subtract From, Minimum, Maximum,Extract,
   Resample, Piecewise Linear
4. Image Overlaying II
   overlaying numbers on a zoomed image
   Piecewise Linear, Multiply, Normalize
   Expand, XOR, Maximum, Add, Gate Data
5. Mask Application
   ultrasound image application
   Copy from Value, Insert Segments, Statistics

1. Color Table
   coloring a black and white logo
   labeling, ASCII to Map, Subtract From, Statistics
   Insert Segments
2. Thresholding
   image segmentation
   >,Statistics
3. Window-Level Contrast Enhancement
   Clip Outside, Normalize, Statistics, Histogram
4. Histogram Stretch Contrast Enhancement
   Stretch, Histogram
5. Histogram Equalization
   Cumulative Histogram, Insert Segments
6. Logarithm Contrast Enhancement
   Insert Segments, Map Data, Data Object Info
7. Logarithm Contrast Enhancement/Scaling
   scaling problem
   Multiply, Logarithm, Piecewise Linear
8. Exponential Contrast Enhancement
   bright microscopic image of tissue cells
   Insert Segments, Map Data, Data Object Info
9. Pseudocolor Applications
   ramp color scale
   Autocolor, Piecewise Linear, Flip, Convert Type
   Pad, Inset
10. Display of Image Attributes
    using histogram of labeled image as colormap
    labeling, Histogram, Copy from Value,
    Insert Segments, Map Data, Autocolor
11. Bit Plane Slicing
    image compression
    Shrink, Stretch, AND

1. DFT: A Pulse Example
   dft interpretation
   Sinusoidal, >=, FFT, Complex to Real,
   Extract, Print Data
2. 2D DFT from 1D DFT
   FFT
3. DFT: Properties
   translation, rotation, addition
   Constant, Pad, Rotate, Translate,
   Resample, FFT
4. DFT: Simple Images
   sinusoid, rectangle, gaussian, impulse
   Constant, Pad, Gaussian, Impulse
   FFT
5. DFT: Pulse Width and Zero-Crossings (Bandwidth)
   dft of width varying pulse
   Constant, Pad, FFT, Statistics, Print Data
6. DFT: Sampling and Aliasing
   maximum sinusoidal frequency
   Sinusoidal, FFT, Magnitudes
7. DFT: Filtering in the Frequency Domain
   low pass, high pass, band pass
   Sinusoidal, >=, Low-Pass, High-Pass,
   Band-Pass, FFT, Real Part
8. DFT: Filtering of Coherent Noise
   coherent noise
   Constant, Circle Image, Inset, FFT,
   Absolute Diff, Magnitudes
9. Convolution Principles
   convolution of a simple image
   linear and shift invariant, simple examples
   Linear Operator, Constant, Impulse,
10. Circular Convolution Theorem
    cyclic or periodic
    Pad, FFT, Linear Operator, Absolute Diff, Multiply
11. DFT: Linear Convolution
    linear or aperiodic
    Shrink, Pad, Import ASCII, FFT, Linear Operator
12. Image Sharpening
    Laplacian filter
    Convert Type, Import ASCII, Print Data,
    Linear Operator, Pad, FFT
13. Correlation
    template matching by correlation
    Linear Operator
14. Interpolation
    frequency interpretation of interpolation
    FFT, Linear Operator, Piecewise Linear,
    Constant, Low Pass, Multiply

1. Inverse Filtering
   ideal deblurring
   FFT, Magnitude, Divide
2. Pseudo-Inverse Filtering
   deblurring with noise
   Convert Type, FFT, Magnitude, Inverse Filter
3. Wiener Filtering
   deblurring with noise
   Convert Type, FFT, Magnitude, Wiener Filter

1. Wavelet Transform
   a compression example
   Wavelet Transform, Extract, Pad, Absolute Diff
2. Wavelets: Frequency Analysis
   decomposition in the frequency domain
   Wavelet Transform, FFT

1. Edge Detection I
   gradient operators
   Linear Operator, Hypotenuse, Inset
2. Edge Detection II
   gradients: Roberts, Sobel, Prewitt, Isotropic
   Gradient Operator
3. Median Filtering
   3x3, 5x5 and 7x7 mask sizes applied to shot noise removal
4. Dilation, Erosion, Opening, Closing
   basic concepts
   Dilation, Erosion, Circle Image, Viff-> Str.El.
5. Contours
   contour of cells
   Erosion, Labeling, Histogram; Str.El. 3x3

1. Feature Extraction
   pieces
   Labeling(MMACH), Shape Analysis, Dilation,
   Erosion, Extract, Pad, Autocolor
2. Classification
   minimum distance classify
   Minimum Distance, Labeling(MMACH), Shape Analysis,
   Dilation, Erosion, Inset, Switch Axes,
   Insert Segments, Map Data, Extract, Pad, Autocolor