| Image Processing Toolbox |
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- What Is the Image Processing Toolbox?
- What Can You Do with the Image Processing Toolbox?
- New Features in Version 2.2
- Related Products
- Post Installation Notes
- About This Manual
- User Experience Levels
- Words You Need to Know
- Typographical Conventions
- Image Processing Toolbox Typographical Conventions
- Image Processing Demos
- MATLAB Newsgroup
- Overview
- Exercise 1 -- Some Basic Topics
- 1. Read and Display an Image
- 2. Check the Image in Memory
- 3. Perform Histogram Equalization
- 4. Write the Image
- 5. Check the Contents of the Newly Written File
- Exercise 2 -- Advanced Topics
- 1. Read and Display An Image
- 2. Perform Block Processing to Approximate the Background
- 3. Display the Background Approximation As a Surface
- 4. Resize the Background Approximation
- 5. Subtract the Background Image from the Original Image
- 6. Adjust the Image Contrast
- 7. Apply Thresholding to the Image
- 8. Use Connected Components Labeling to Determine the Number of Objects in the Image
- 9. Examine an Object
- 10. Compute Feature Measurements of Objects in the Image
- 11. Compute Statistical Properties of Objects in the Image
- Where to Go From Here
- Online Help
- Toolbox Demos
- Overview
- Words You Need to Know
- Images in MATLAB and the Image Processing Toolbox
- Storage Classes in the Toolbox
- Image Types in the Toolbox
- Indexed Images
- Intensity Images
- Binary Images
- RGB Images
- Multiframe Image Arrays
- Summary of Image Types and Numeric Classes
- Working with Image Data
- Reading a Graphics Image
- Writing a Graphics Image
- Querying a Graphics File
- Converting The Image Type of Images
- Working with uint8 and uint16 Data
- Converting The Storage Class of Images
- Converting the Graphics File Format of an Image
- Coordinate Systems
- Pixel Coordinates
- Spatial Coordinates
- Overview
- Words You Need to Know
- Displaying Images with imshow
- Displaying Indexed Images
- Displaying Intensity Images
- Displaying Binary Images
- Displaying RGB Images
- Displaying Images Directly from Disk
- Special Display Techniques
- Adding a Colorbar
- Displaying Multiframe Images
- Displaying Multiple Images
- Setting the Preferences for imshow
- Zooming in on a Region of an Image
- Texture Mapping
- Printing Images
- Troubleshooting
- Overview
- Words You Need to Know
- Interpolation
- Image Types
- Image Resizing
- Image Rotation
- Image Cropping
- Overview
- Words You Need to Know
- Types of Block Processing Operations
- Sliding Neighborhood Operations
- Padding of Borders
- Linear and Nonlinear Filtering
- Distinct Block Operations
- Overlap
- Column Processing
- Sliding Neighborhoods
- Distinct Blocks
- Overview
- Words You Need to Know
- Linear Filtering
- Convolution
- Padding of Borders
- The filter2 Function
- Separability
- Higher-Dimensional Convolution
- Using Predefined Filter Types
- Filter Design
- FIR Filters
- Frequency Transformation Method
- Frequency Sampling Method
- Windowing Method
- Creating the Desired Frequency Response Matrix
- Computing the Frequency Response of a Filter
- Overview
- Words You Need to Know
- Fourier Transform
- Definition of Fourier Transform
- The Discrete Fourier Transform
- Applications
- Discrete Cosine Transform
- The DCT Transform Matrix
- The DCT and Image Compression
- Radon Transform
- Using the Radon Transform to Detect Lines
- The Inverse Radon Transform
- Overview
- Words You Need to Know
- Pixel Values and Statistics
- Pixel Selection
- Intensity Profile
- Image Contours
- Image Histogram
- Summary Statistics
- Feature Measurement
- Image Analysis
- Edge Detection
- Quadtree Decomposition
- Image Enhancement
- Intensity Adjustment
- Noise Removal
- Overview
- Words You Need to Know
- Neighborhoods
- Padding of Borders
- Displaying Binary Images
- Morphological Operations
- Dilation and Erosion
- Related Operations
- Object-Based Operations
- 4- and 8-Connected Neighborhoods
- Perimeter Determination
- Flood Fill
- Connected-Components Labeling
- Object Selection
- Feature Measurement
- Image Area
- Euler Number
- Lookup Table Operations
- Overview
- Words You Need to Know
- Specifying a Region of Interest
- Selecting a Polygon
- Other Selection Methods
- Filtering a Region
- Filling a Region
- Overview
- Words You Need to Know
- Working with Different Screen Bit Depths
- Reducing the Number of Colors in an Image
- Using rgb2ind
- Using imapprox
- Dithering
- Converting to Other Color Spaces
- NTSC Color Space
- YCbCr Color Space
- HSV Color Space
- Functions by Category
- applylut
- bestblk
- blkproc
- brighten
- bwarea
- bweuler
- bwfill
- bwlabel
- bwmorph
- bwperim
- bwselect
- cmpermute
- cmunique
- col2im
- colfilt
- colorbar
- conv2
- convmtx2
- convn
- corr2
- dct2
- dctmtx
- dilate
- dither
- double
- edge
- erode
- fft2
- fftn
- fftshift
- filter2
- freqspace
- freqz2
- fsamp2
- fspecial
- ftrans2
- fwind1
- fwind2
- getimage
- gray2ind
- grayslice
- histeq
- hsv2rgb
- idct2
- ifft2
- ifftn
- im2bw
- im2col
- im2double
- im2uint8
- im2uint16
- imadjust
- imapprox
- imcontour
- imcrop
- imfeature
- imfinfo
- imhist
- immovie
- imnoise
- impixel
- improfile
- imread
- imresize
- imrotate
- imshow
- imwrite
- ind2gray
- ind2rgb
- iptgetpref
- iptsetpref
- iradon
- isbw
- isgray
- isind
- isrgb
- makelut
- mat2gray
- mean2
- medfilt2
- montage
- nlfilter
- ntsc2rgb
- ordfilt2
- phantom
- pixval
- qtdecomp
- qtgetblk
- qtsetblk
- radon
- rgb2gray
- rgb2hsv
- rgb2ind
- rgb2ntsc
- rgb2ycbcr
- rgbplot
- roicolor
- roifill
- roifilt2
- roipoly
- std2
- subimage
- truesize
- uint8
- uint16
- warp
- wiener2
- ycbcr2rgb
- zoom
- Passing an M-File Function to a Function Function
- Passing an Inline Object to a Function Function
- Passing a String to a Function Function
| | Getting Started | |