Image Processing Toolbox™User's Guide

Getting Started
	Image Processing Toolbox Product Description
		Key Features
	Compilability
	Basic Image Import, Processing, and Export
	Correct Nonuniform Illumination and Analyze Foreground Objects
	Acknowledgments
Introduction
	Images in MATLAB
	Image Coordinate Systems
		Pixel Indices
		Spatial Coordinates
	Define World Coordinate System of Image
		Define Spatial Referencing Objects
		Specify Minimum and Maximum Image Extent
	Shift X- and Y-Coordinate Range of Displayed Image
	Image Types in the Toolbox
		Binary Images
		Indexed Images
		Grayscale Images
		Truecolor Images
		HDR Images
		Multispectral and Hyperspectral Images
		Label Images
	Display Separated Color Channels of RGB Image
	Convert Between Image Types
	Convert Image Data Between Classes
		Overview of Image Class Conversions
		Losing Information in Conversions
		Converting Indexed Images
	Perform an Operation on a Sequence of Images
	Detecting Cars in a Video of Traffic
	Process Folder of Images Using Image Batch Processor App
	Process Large Set of Images Using MapReduce Framework and Hadoop
	Work with Image Sequences as Multidimensional Arrays
		Create Multidimensional Array Representing Image Sequence
		Display Image Sequences
		Process Image Sequences
	Image Arithmetic Functions
	Image Arithmetic Clipping Rules
	Nest Calls to Image Arithmetic Functions
	Find Vegetation in a Multispectral Image
Reading and Writing Image Data
	Read Image Data into the Workspace
	Read Multiple Images from a Single Graphics File
	Read and Write 1-Bit Binary Images
	Write Image Data to File in Graphics Format
	DICOM Support in Image Processing Toolbox
	Read Metadata from DICOM Files
		Private DICOM Metadata
		Create Your Own Copy of DICOM Dictionary
	Read Image Data from DICOM Files
		View DICOM Images
	Write Image Data to DICOM Files
		Include Metadata with Image Data
		Specify Value Representation
	Remove Confidential Information from DICOM File
	Create New DICOM Series
	Create Image Datastore Containing DICOM Images
	Create Image Datastore Containing Single and Multi-File DICOM Volumes
	Mayo Analyze 7.5 Files
	Interfile Files
	End-to-End Implementation of Digital Camera Processing Pipeline
	Work with High Dynamic Range Images
		Read HDR Image
		Display and Process HDR Image
		Create High Dynamic Range Image
		Write High Dynamic Range Image to File
	Display High Dynamic Range Image
Displaying and Exploring Images
	Image Display and Exploration Overview
	Display an Image in Figure Window
		Overview
		Specifying the Initial Image Magnification
		Controlling the Appearance of the Figure
	Display Multiple Images
		Display Multiple Images in Separate Figure Windows
		Display Multiple Images in a Montage
		Display Images Individually in the Same Figure
		Compare a Pair of Images
	View Thumbnails of Images in Folder or Datastore
	Get Started with Image Viewer App
		Open Image Viewer App
		Navigate Image in Image Viewer App
		Get Information about Image Data
		Modify Image Data
		Save and Export Results
	Get Pixel Information in Image Viewer App
		Determine Individual Pixel Values in Image Viewer
		Determine Pixel Values in an Image Region
		Determine Image Display Range in Image Viewer
	Measure Distance Between Pixels in Image Viewer App
		Determine Distance Between Pixels Using Distance Tool
		Export Endpoint and Distance Data
		Customize the Appearance of the Distance Tool
	Adjust Image Contrast in Image Viewer App
		Adjust Contrast and Brightness using Adjust Contrast Tool
		Adjust Contrast and Brightness Using Window/Level Tool
		Make Contrast Adjustments Permanent
	Crop Image Using Image Viewer App
	Explore 3-D Volumetric Data with Volume Viewer App
		Load Volume Data into the Volume Viewer
		View the Volume Data in the Volume Viewer
		Adjust View of Volume Data in Volume Viewer
		Refine the View with the Rendering Editor
		Save Volume Viewer Rendering and Camera Configuration Settings
	Explore 3-D Labeled Volumetric Data with Volume Viewer App
		Load Labeled Volume and Intensity Volume into Volume Viewer
		View Labeled Volume in Volume Viewer
		Embed Labeled Volume with Intensity Volume
	View Image Sequences in Video Viewer App
		View MRI Sequence Using Video Viewer App
		Configure Video Viewer App
		Specifying the Frame Rate
		Specify Color Map
		Get Information about an Image Sequence
	Convert Multiframe Image to Movie
	Display Different Image Types
		Display Indexed Images
		Display Grayscale Images
		Display Binary Images
		Display Truecolor Images
	Add Color Bar to Displayed Grayscale Image
	Print Images
		Graphics Object Properties That Impact Printing
	Manage Display Preferences
		Retrieve Values of Toolbox Preferences
		Set Values of Toolbox Preferences
Building GUIs with Modular Tools
	Interactive Image Viewing and Processing Tools
	Interactive Tool Workflow
		Display Target Image in Figure Window
		Create the Tool
		Position Tools
		Add Navigation Aids
		Customize Tool Interactivity
	Add Scroll Panel to Figure
	Get Handle to Target Image
	Create Pixel Region Tool
	Build App to Display Pixel Information
	Build App for Navigating Large Images
	Build Image Comparison Tool
	Create Angle Measurement Tool Using ROI Objects
Geometric Transformations
	Resize an Image with imresize Function
	Rotate an Image
	Crop an Image
	Translate an Image using imtranslate Function
	2-D and 3-D Geometric Transformation Process Overview
		Create Geometric Transformation Object
		Perform the Geometric Transformation
	Matrix Representation of Geometric Transformations
		2-D Affine Transformations
		2-D Projective Transformations
		Create Composite 2-D Affine Transformations
		3-D Affine Transformations
	Specify Fill Values in Geometric Transformation Output
	Perform Simple 2-D Translation Transformation
	N-Dimensional Spatial Transformations
	Register Two Images Using Spatial Referencing to Enhance Display
	Create a Gallery of Transformed Images
	Exploring a Conformal Mapping
	Exploring Slices from a 3-Dimensional MRI Data Set
	Padding and Shearing an Image Simultaneously
Image Registration
	Approaches to Registering Images
		Registration Estimator App
		Intensity-Based Automatic Image Registration
		Control Point Registration
		Automated Feature Detection and Matching
	Register Images Using Registration Estimator App
	Load Images, Spatial Referencing Information, and Initial Transformation
		Load Images from File or Workspace
		Provide Spatial Referencing Information
		Provide an Initial Geometric Transformation
	Tune Registration Settings in Registration Estimator App
		Geometric Transformations Supported by Registration Estimator App
		Feature-Based Registration Settings
		Intensity-Based Registration Settings
		Nonrigid and Post-Processing Settings
	Export Results from Registration Estimator App
		Export Results to the Workspace
		Generate a Function
	Techniques Supported by Registration Estimator App
		Feature-Based Registration
		Intensity-Based Registration
		Nonrigid Registration
	Intensity-Based Automatic Image Registration
	Create an Optimizer and Metric for Intensity-Based Image Registration
	Use Phase Correlation as Preprocessing Step in Registration
	Register Multimodal MRI Images
	Register Multimodal 3-D Medical Images
	Registering an Image Using Normalized Cross-Correlation
	Control Point Registration
	Geometric Transformation Types for Control Point Registration
	Control Point Selection Procedure
	Start the Control Point Selection Tool
	Find Visual Elements Common to Both Images
		Use Scroll Bars to View Other Parts of an Image
		Use the Detail Rectangle to Change the View
		Pan the Image Displayed in the Detail Window
		Zoom In and Out on an Image
		Specify the Magnification of the Images
		Lock the Relative Magnification of the Moving and Fixed Images
	Select Matching Control Point Pairs
		Pick Control Point Pairs Manually
		Use Control Point Prediction
		Move Control Points
		Delete Control Points
	Export Control Points to the Workspace
	Find Image Rotation and Scale
	Use Cross-Correlation to Improve Control Point Placement
	Register Images with Projection Distortion Using Control Points
Designing and Implementing Linear Filters for Image Data
	What Is Image Filtering in the Spatial Domain?
		Convolution
		Correlation
	Integral Image
	Filter Grayscale and Truecolor (RGB) Images using imfilter Function
	imfilter Boundary Padding Options
	Filter Images Using Predefined Filter
	Generate HDL Code for Image Sharpening
	What is Guided Image Filtering?
	Perform Flash/No-flash Denoising with Guided Filter
	Segment Thermographic Image after Edge-Preserving Filtering
	Apply Multiple Filters to Integral Image
	Reduce Noise in Image Gradients
	Design Linear Filters in the Frequency Domain
		Two-Dimensional Finite Impulse Response (FIR) Filters
		Transform 1-D FIR Filter to 2-D FIR Filter
		Frequency Sampling Method
		Windowing Method
		Creating the Desired Frequency Response Matrix
		Computing the Frequency Response of a Filter
Transforms
	Fourier Transform
		Definition of Fourier Transform
		Discrete Fourier Transform
		Applications of the Fourier Transform
	Discrete Cosine Transform
		DCT Definition
		The DCT Transform Matrix
		Image Compression with the Discrete Cosine Transform
	Hough Transform
		Detect Lines in Images Using Hough
	Radon Transform
		Plot the Radon Transform of an Image
		Viewing the Radon Transform as an Image
	Detect Lines Using the Radon Transform
	The Inverse Radon Transformation
		Inverse Radon Transform Definition
		Reconstructing an Image from Parallel Projection Data
	Fan-Beam Projection
		Image Reconstruction from Fan-Beam Projection Data
		Reconstruct Image using Inverse Fanbeam Projection
	Reconstructing an Image from Projection Data
Morphological Operations
	Types of Morphological Operations
		Morphological Dilation and Erosion
		Operations Based on Dilation and Erosion
	Structuring Elements
		Determine the Origin of a Structuring Element
		Structuring Element Decomposition
	Border Padding for Morphology
	Morphological Reconstruction
		Understanding the Marker and Mask
		Finding Peaks and Valleys
	Pixel Connectivity
		Defining Connectivity in an Image
		Choosing a Connectivity
		Specifying Custom Connectivities
	Lookup Table Operations
		Creating a Lookup Table
		Using a Lookup Table
	Dilate an Image to Enlarge a Shape
	Remove Thin Lines Using Erosion
	Use Morphological Opening to Extract Large Image Features
	Flood-Fill Operations
		Specifying Connectivity
		Specifying the Starting Point
		Filling Holes
	Detect Cell Using Edge Detection and Morphology
	Granulometry of Snowflakes
	Distance Transform of a Binary Image
	Label and Measure Connected Components in a Binary Image
		Detect Connected Components
		Label Connected Components
		Select Objects in a Binary Image
		Measure Properties of Connected Components
Analyzing and Enhancing Images
	Pixel Values
		Determine Values of Individual Pixels in Images
	Intensity Profile of Images
		Create an Intensity Profile of an Image
		Create Intensity Profile of an RGB Image
	Contour Plot of Image Data
		Create Contour Plot of Image Data
	Measuring Regions in Grayscale Images
	Finding the Length of a Pendulum in Motion
	Create Image Histogram
	Image Mean, Standard Deviation, and Correlation Coefficient
	Edge Detection
		Detect Edges in Images
	Boundary Tracing in Images
		Trace Boundaries of Objects in Images
		Select First Step and Direction for Tracing
	Quadtree Decomposition
		Perform Quadtree Decomposition on an Image
	Detect and Measure Circular Objects in an Image
	Identifying Round Objects
	Measuring Angle of Intersection
	Measuring the Radius of a Roll of Tape
	Calculate Statistical Measures of Texture
	Texture Analysis Using the Gray-Level Co-Occurrence Matrix (GLCM)
	Create a Gray-Level Co-Occurrence Matrix
	Specify Offset Used in GLCM Calculation
	Derive Statistics from GLCM and Plot Correlation
	Adjust Image Intensity Values to Specified Range
	Gamma Correction
		Specify Gamma when Adjusting Contrast
	Contrast Enhancement Techniques
	Specify Contrast Adjustment Limits
		Specify Contast Adjustment Limits as Range
		Set Image Intensity Adjustment Limits Automatically
	Histogram Equalization
		Adjust Intensity Values Using Histogram Equalization
		Plot Transformation Curve for Histogram Equalization
	Adaptive Histogram Equalization
		Adjust Contrast using Adaptive Histogram Equalization
	Enhance Color Separation Using Decorrelation Stretching
		Simple Decorrelation Stretching
		Linear Contrast Stretching
		Decorrelation Stretch with Linear Contrast Stretch
	Enhance Multispectral Color Composite Images
	Low-Light Image Enhancement
	Increase Filter Strength Radially Outward
	Apply Gaussian Smoothing Filters to Images
	Noise Removal
		Remove Noise by Linear Filtering
		Remove Noise Using an Averaging Filter and a Median Filter
		Remove Noise By Adaptive Filtering
	Compute 3-D Superpixels of Input Volumetric Intensity Image
	Image Quality Metrics
		Full-Reference Quality Metrics
		No-Reference Quality Metrics
	Train and Use No-Reference Quality Assessment Model
		NIQE Workflow
		BRISQUE Workflow
	Compare No Reference Image Quality Metrics
	Obtain Local Structural Similarity Index
	Compare Image Quality at Various Compression Levels
	Anatomy of Imatest Extended eSFR Chart
		Slanted Edge Features
		Gray Patch Features
		Color Patch Features
		Registration Markers
	Evaluate Quality Metrics on eSFR Test Chart
	Correct Colors Using Color Correction Matrix
	Install Sample Data Using Add-On Explorer
ROI-Based Processing
	Create a Binary Mask
		Create a Binary Mask from a Grayscale Image
		Create Binary Mask Using an ROI Function
		Create Binary Mask Based on Color Values
		Create Binary Mask Without an Associated Image
	ROI Creation Overview
		Create ROI Using Creation Convenience Functions
		Create ROI Using draw Function
		Using ROIs in Apps Created with App Designer
	ROI Migration
		ROI Object Migration
		ROI Object Function Migration
		ROI Events
	Overview of ROI Filtering
	Sharpen Region of Interest in an Image
	Apply Custom Filter to Region of Interest in Image
	Fill Region of Interest in an Image
	Calculate Properties of Image Regions Using Image Region Analyzer
	Filter Images on Properties Using Image Region Analyzer App
	Create Image Comparison Tool Using ROIs
	Use Freehand ROIs to Refine Segmentation Masks
	Rotate Image Interactively Using Rectangle ROI
	Subsample or Simplify a Freehand ROI
	Measure Distances in an Image
	Use Polyline to Create Angle Measurement Tool
	Create Freehand ROI Editing Tool
	Use Wait Function After Drawing ROI
	Interactive Image Inpainting Using Exemplar Matching
Image Segmentation
	Texture Segmentation Using Gabor Filters
	Texture Segmentation Using Texture Filters
	Color-Based Segmentation Using the L*a*b* Color Space
	Color-Based Segmentation Using K-Means Clustering
	Marker-Controlled Watershed Segmentation
	Segment Image and Create Mask Using Color Thresholder App
	Acquire Live Images in the Color Thresholder App
	Image Segmentation Using Point Clouds in the Color Thresholder App
	Getting Started with Image Segmenter App
		Open Image Segmenter App and Load Data
		Create and Add Regions to Segmented Mask
		Refine Segmented Mask
		Export Segmentation Results
	Segment Image Using Thresholding in Image Segmenter
	Segment Image By Drawing Regions Using Image Segmenter
	Segment Image Using Active Contours in Image Segmenter
	Refine Segmentation Using Morphology in Image Segmenter
	Segment Image Using Graph Cut in Image Segmenter
	Segment Image Using Local Graph Cut (Grabcut) in Image Segmenter
	Segment Image Using Find Circles in Image Segmenter
	Segment Image Using Auto Cluster in Image Segmenter
	Plot Land Classification with Color Features and Superpixels
	Segment Lungs from 3-D Chest Scan
	Create Binary Mask Using Volume Segmenter
	Create Semantic Segmentation Using Volume Segmenter
	Work with Blocked Images Using the Volume Segmenter
Image Deblurring
	Image Deblurring
		Deblurring Functions
	Deblur Images Using a Wiener Filter
	Deblur Images Using a Regularized Filter
	Adapt the Lucy-Richardson Deconvolution for Various Image Distortions
		Reduce the Effect of Noise Amplification
		Account for Nonuniform Image Quality
		Handle Camera Read-Out Noise
		Handling Undersampled Images
		Refine the Result
	Deblurring Images Using the Lucy-Richardson Algorithm
	Adapt Blind Deconvolution for Various Image Distortions
		Deblur images using blind deconvolution
		Refining the Result
	Deblurring Images Using the Blind Deconvolution Algorithm
	Create Your Own Deblurring Functions
	Avoid Ringing in Deblurred Images
Color
	Display Colors
	Reduce the Number of Colors in an Image
		Reduce Colors of Truecolor Image Using Color Approximation
		Reduce Colors of Indexed Image Using imapprox
		Reduce Colors Using Dithering
	Profile-Based Color Space Conversions
		Read ICC Profiles
		Write ICC Profile Information to a File
		Convert RGB to CMYK Using ICC Profiles
		What is Rendering Intent in Profile-Based Conversions?
	Device-Independent Color Spaces
		Convert Between Device-Independent Color Spaces
		Color Space Data Encodings
	Understanding Color Spaces and Color Space Conversion
		RGB
		HSV
		CIE 1976 XYZ and CIE 1976 L*a*b*
		YCbCr
		YIQ
	Convert Between RGB and HSV Color Spaces
	Determine If L*a*b* Value Is in RGB Gamut
	Comparison of Auto White Balance Algorithms
	Calculate CIE94 Color Difference of Colors on Test Chart
Blocked Image Processing
	Set Up Spatial Referencing for Blocked Images
	Process Blocked Images Efficiently Using Partial Images or Lower Resolutions
	Process Blocked Images Efficiently Using Mask
	Explore Blocked Image Details with Interactive ROIs
	Warp Blocked Image at Coarse and Fine Resolution Levels
	Create Labeled Blocked Image from ROIs and Masks
	Read Whole-slide Images with Custom Blocked Image Adapter
Neighborhood and Block Operations
	Neighborhood or Block Processing: An Overview
	Sliding Neighborhood Operations
		Determine the Center Pixel
		General Algorithm of Sliding Neighborhood Operations
		Border Padding Behavior in Sliding Neighborhood Operations
		Implementing Linear and Nonlinear Filtering as Sliding Neighborhood Operations
	Distinct Block Processing
		Implement Block Processing Using the blockproc Function
		Apply Padding
	Block Size and Performance
		TIFF Image Characteristics
		Choose Block Size to Optimize blockproc Performance
	Parallel Block Processing on Large Image Files
		What is Parallel Block Processing?
		When to Use Parallel Block Processing
		How to Use Parallel Block Processing
	Perform Block Processing on Image Files in Unsupported Formats
		Learning More About the LAN File Format
		Parsing the Header
		Reading the File
		Examining the LanAdapter Class
		Using the LanAdapter Class with blockproc
	Use Column-wise Processing to Speed Up Sliding Neighborhood or Distinct Block Operations
		Using Column Processing with Sliding Neighborhood Operations
		Using Column Processing with Distinct Block Operations
	Block Processing Large Images
	Compute Statistics for Large Images
Deep Learning
	Train and Apply Denoising Neural Networks
		Remove Gaussian Noise Using Pretrained Network
		Train a Denoising Network Using Built-In Layers
		Train Fully Customized Denoising Neural Network
	Get Started with GANs for Image-to-Image Translation
		Select a GAN
		Create GAN Networks
		Train GAN Network
	Create Modular Neural Networks
		Create Encoder and Decoder Modules
		Create Networks from Encoder and Decoder Modules
	Remove Noise from Color Image Using Pretrained Neural Network
	Single Image Super-Resolution Using Deep Learning
	JPEG Image Deblocking Using Deep Learning
	Image Processing Operator Approximation Using Deep Learning
	Develop Raw Camera Processing Pipeline Using Deep Learning
	Semantic Segmentation of Multispectral Images Using Deep Learning
	3-D Brain Tumor Segmentation Using Deep Learning
	Classify Large Multiresolution Images Using blockedImage and Deep Learning
	Neural Style Transfer Using Deep Learning
	Unsupervised Day-To-Dusk Image Translation Using UNIT
	Quantify Image Quality Using Neural Image Assessment
Hyperspectral Image Processing
	Getting Started with Hyperspectral Image Processing
		Representing Hyperspectral Data
		Preprocessing
		Spectral Unmixing
		Spectral Matching
		Applications
	Hyperspectral Data Correction
		Radiometric Calibration
		Atmospheric Correction
	Explore Hyperspectral Data in the Hyperspectral Viewer
	Hyperspectral Image Analysis Using Maximum Abundance Classification
	Classify Hyperspectral Image Using Library Signatures and SAM
	Endmember Material Identification Using Spectral Library
	Target Detection Using Spectral Signature Matching
	Identify Vegetation Regions Using Interactive NDVI Thresholding
	Classify Hyperspectral Images Using Deep Learning
Code Generation for Image Processing Toolbox Functions
	Code Generation for Image Processing
		Code Generation Using a Shared Library
	List of Supported Functions with Usage Notes
	Generate Code for Object Detection
GPU Computing with Image Processing Toolbox Functions
	Image Processing on a GPU
	Perform Thresholding and Morphological Operations on GPU
	Perform Pixel-Based Operations on GPU