Digital Image Processing: Part II

This book (vol.1 and vol.2) introduces the fundamental theories of modern digital image processing including intensity transformations, filtering in the frequency and spatial domain, restoration, colour processing, morphological operations, and segmentation. It aims to help the students, scientists, and practitioners to understand the concepts through illustrations and examples

Digital image processing is an important research area. The techniques developed in this area so far require to be summarized in an appropriate way. In this book, the fundamental theories of these techniques will be introduced. Particularly, their applications in the image enhancement are briefly summarized. The entire book consists of three chapters, which will be subsequently introduced.

Chapter 1 reveals the challenges in colour image processing in addition to potential solutions to individual problems. Chapter 2 summarises state of the art techniques for morphological process, and chapter 3 illustrates the established segmentation approach.

Prefaces
1. Colour Image Processing
1.1 Colour Fundamentals
1.2 Colour Space
1.3 Colour Image Processing
1.4 Smoothing and sharpening
1.5 Image segmentation
1.6 Colour Image Compression
Summary
References
Problems

2. Morphological Image Processing
2.1 Mathematical morphology
2.1.1 Introduction
2.1.1 Binary images
2.1.2 Operators in set theory
2.1.3 Boolean logical operators
2.1.4 Structure element
2.2 Dilation and Erosion
2.2.1 Dilation
2.2.2 Erosion
2.2.3 Properties of dilation and erosion
2.2.4 Morphological gradient
2.3 Opening and closing
2.3.1 Opening
2.3.2 Closing
2.3.3 Properties of opening and closing
2.3.4 Top-hat transformation
2.4 Hit-or-miss
2.5 Thinning and thicken
2.6 Skeleton
2.7 Pruning
2.8 Morphological reconstruction
2.8.1 Definition of morphological reconstruction
2.8.2 The choice of maker and mask images
Summary
References and further reading
Problems

3. Image Segmentation
3.1 Introduction
3.2 Image pre-processing – correcting image defects
3.2.1 Image smooth by median filter
3.2.2 Background correction by top-hat filter
3.2.3 Illumination correction by low-pass filter
3.2.4 Protocol of pre-process noisy image
3.3 Thresholding
3.3.1 Fundamentals of image thresholding
3.3.2 Global optimal thresholding
3.3.3 Adaptive local thresholding
3.3.4 Multiple thresholding
3.4 Line and edge detection
3.4.1 Line detection
3.4.2 Hough transformation for line detection
3.4.3 Edge filter operators
3.4.4 Border tracing - detecting edges of predefined operators
3.5 Segmentation using morphological watersheds
3.5.1 Watershed transformation
3.5.2 Distance transform
3.5.3 Watershed segmentation using the gradient field
3.5.4 Marker-controlled watershed segmentation
3.6 Region-based segmentation
3.6.1 Seeded region growing
3.6.2 Region splitting and merging
3.7 Texture-based segmentation
3.8 Segmentation by active contour
3.9 Object-oriented image segmentation
3.10 Colour image segmentation
Summary
References and further reading
Problems