- Visual Media Processing Using MATLAB Beginner's Guide
- Table of Contents
- Visual Media Processing Using MATLAB Beginner's Guide
- Credits
- About the Author
- About the Reviewers
- www.PacktPub.com
- Preface
- 1. Basic Image Manipulations
- Getting acquainted with the MATLAB environment
- The ribbon
- The editor
- Importing and displaying an image
- Time for action – importing and displaying an image
- Time for action – using imtool to extract useful information
- Applying geometric transformations
- Time for action – rotating an image and displaying the result
- Time for action – mirroring an image and displaying the result
- Time for action – cropping and resizing an image, then saving it as BMP
- Summary
- 2. Working with Pixels In Grayscale Images
- Accessing image pixels and changing their values
- Time for action – whiten an area and blacken another
- Thresholding an image
- Calculating and displaying histograms with imhist
- Histogram equalization for contrast enhancement
- Contrasting enhancement using imadjust
- Contrasting enhancement using imcontrast
- Adaptive histogram equalization using adapthisteq
- Custom functions for complex tasks
- Time for action – using imtool to pinpoint differences
- Restoring old photographs
- Time for action – restoring your ancestors' photographs
- Summary
- 3. Morphological Operations and Object Analysis
- The importance of binary images
- Time for action – understanding the value of thresholding
- Enlarging and shrinking a region of interest
- Time for action – using dilation and erosion to refine ROIs
- Altering structuring elements from strel to suit our needs
- Time for action – ROI refinement using strel
- Manually defining a non-rectangular ROI
- Time for action – making a custom object eraser function
- Analyzing objects in an image
- Summary
- 4. Working with Color Images
- An introduction to color image processing
- Basic color image manipulations
- Setting a rectangular area to a specified color
- Time for action – repainting two areas in a color image
- Thresholding color images
- Time for action – isolating the red pixels in an image
- Achieving color masking
- Time for action – color isolation
- The importance of different color spaces
- Time for action – color space transformation
- CIE-L*a*b* for more efficient color masking
- Time for action – color isolation using CIE-L*a*b*
- Fixing illumination issues in RGB color images
- Fixing illumination issues in CIE-L*a*b*
- A practical example – red eye reduction
- Time for action – writing a function for red eye reduction
- Taking advantage of eye circularity
- Time for action – automating our function for red eye reduction
- Summary
- 5. 2-Dimensional Image Filtering
- An introduction to image filtering
- Processing neighborhoods of pixels
- The basics of convolution
- The ugly mathematical truth
- Time for action – applying averaging filters in images
- Alternatives to convolution
- Using imfilter
- Creating filters with fspecial
- Different ways to blur an image
- Time for action – how much blurring is enough
- Time to make art using blurring
- Time for action – creating the bokeh effect in an image
- Removing noise using blurring
- Time for action – trying to remove different types of noise
- The importance of the median filter
- Time for action – removing salt & pepper with medfilt2
- Bringing back the details
- Time for action – enhancing the edges in our images
- Brighten up the lights
- Time for action – brighten up the lights in our soldier picture
- Summary
- 6. Mixing Images for Science or Art
- The importance of mixing or combining images
- Using multispectral imaging
- Loading and manipulating the multispectral images
- Time for action – visible spectrum from a multiband image of Rio
- Time for action – working with invisible spectrums
- Creating composite images
- Time for action – cloning the seagull
- One step beyond – blending selected image regions
- Time for action – directing a threatening scene
- Creating High Dynamic Range images
- Time for action – composing your own HDR images
- Stitching images for the creation of panoramas
- Time for action – basic approach to panorama stitching
- Summary
- 7. Adding Motion – From Static Images to Digital Videos
- An introduction to digital videos
- The meaning of frames
- Loading videos in MATLAB
- Playing back videos in MATLAB
- Time for action – reading and playing back a video
- Making videos from static images
- Time for action – constructing and saving a video
- Inspecting a video using montage
- Time for action – don't wait for the ball
- A tool just for your playback needs – implay
- Creating time-lapse videos
- Time for action – time-lapsing a regular video
- Saving your time-lapse videos in a gif file
- Summary
- 8. Acquiring and Processing Videos
- Using MATLAB for digital video recording
- Time for action – capturing a video using a firewire connection
- The importance of video compression
- Working with uncompressed videos
- Time for action – making an edge detection video
- Acquiring frames for time-lapse videos
- Time for action – using MATLAB as an intervalometer
- Real-time processing of time-lapse videos
- Time for action – creating time-lapses with isolated colors
- Real-time processing of normal videos
- Time for action – adjusting the contrast of the video
- Time for action – adding preview in our code
- Summary
- 9. Spatiotemporal Video Processing
- Basic video processing with MATLAB
- Time for action – loading, cropping, resizing, and saving a video
- Time for action – reducing the blocking effect
- Deinterlacing videos in MATLAB
- Deinterlacing with the Computer Vision System Toolbox
- Time for action – deinterlacing a video using the vision toolbox
- Deinterlacing with the custom functions
- Time for action – deinterlacing with line repetition
- Time for action – deinterlacing with the scan line interpolation
- Inter-frame filtering for the deinterlacing tasks
- Time for action – deinterlacing with field merging
- Temporal deinterlacing by field averaging
- Time for action – deinterlacing with field averaging
- Mixing intra-frame and inter-frame deinterlacing
- Time for action – vertical and temporal interpolation method
- Adding a new dimension to the filters
- Time for action – implementing a spatiotemporal averaging filter
- Time for action – spatiotemporal averaging filter with the convn function
- Summary
- 10. From Beginner to Expert – Handling Motion and 3-D
- Detecting and estimating motion in videos
- Time for action – detecting a moving object in a still scene
- Time for action – detecting motion in a complex scene
- Estimating the motion
- Time for action – tracking people with Horn-Schunck optical flow
- Time for action – warping frames using optical flow
- Compensating camera motion using feature tracking
- Time for action – tracking feature points for motion compensation of a shaky video
- Working with stereoscopic images
- Time for action – creating a 3-D video from left and right videos
- Time for action – creating a 3-D video from a regular one
- Summary
- A. Pop Quiz Answers
- Chapter 1, Basic Image Manupulation
- Chapter 2, Working with Pixels in Grayscale Images
- Chapter 3, Morphological Operations and Object Analysis
- Chapter 4, Working with Color Images
- Chapter 5, 2-Dimensional Image Filtering
- Chapter 6, Mixing Images for Science or Art
- Chapter 7, Adding Motion – From Static Images to Digital Videos
- Chapter 8, Acquiring and Processing Videos
- Chapter 9, Spatiotemporal Video Processing
- Chapter 10, From Beginner to Expert – Handling Motion and 3-D
- Index
This chapter included several useful techniques to manipulate the values of grayscale image pixels. At the same time, it provided a first, hopefully gentle, introduction to writing and running your own scripts and functions in MATLAB. More specifically, you have been taught:
- How to change pixel values in a rectangular area using
for loops, or indexing - How to write and execute a script that alters the brightness in specified rectangular areas of an image
- How to threshold an image using
for loops - How to threshold an image using indexing
- How to threshold an image using
im2bw - How to perform thresholding using an automatically derived threshold
- How to calculate and display the histogram of a grayscale image
- How to perform histogram equalization using
histeq - How to perform contrast enhancement using
imadjust - How to perform contrast enhancement using
imcontrast - How to perform adaptive histogram equalization using
adapthisteq - How to write functions that use all the methods described in this chapter on practical examples
The next chapter will introduce you to morphological operations and their importance in image processing. Some methods already presented will be combined with the morphological operations to enhance images, or segment useful areas. Once finishing it, you will be able to perform extremely useful tasks that are applied both in computational photography and in machine vision applications.
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