Chapter 1 Introduction 1 1 Images and Pictures

Chapter 1: Introduction 1. 1. Images and Pictures An image is worth thousands of word 1 -1

1. 2 Image processing – change the nature of an image Objectives: (a) human interpretation (b) machine perception (A) Human interpretation • Image sharpening 1 -2

• Noise removal • Deblurring 1 -3

Before After 4

Before After 5

For you, . . . not much can be done! 6

(B) Machine perception Input image Edge detection Image segmentation 1 -7

Example: scene understanding Thresholding, Noise removal Group ─ form significant regions Cluster ─ associate with objects Segment ─ locate primary areas Edge detection , Edge following. . . Edge detection Edge following Segmentation Grouping, Clustering Input image Thresholding 8

Three levels of image processing: • Low-level processing – e. g. , threshold, noise removal (smoothing) contrast enhancement (sharpening) • Mid-level processing – e. g. , grouping, clustering, edge detection, image segmentation • High-level processing – e. g. , object recognition scene understanding 1 -9

1. 3 Image Acquisition and Sampling 1. 3. 1 Image Acquisition • Human eye • Cameras 1 -10

• Digital cameras CCD (charge-coupled device) cameras, CMOS (complementary metal oxide semiconductor) camera Image plane Sensor array Image array 1 -11

1. 3. 2 Sampling -- transforms a continuous function into a discrete one • Spatial Resolution 1 -12

• Grayscale resolution (Quantization) False contours 1 -13

1. 4 Images and Digital Images • Imaging model 1 -14

Scene: a 3 -D continuous function, g(x, y, z) Image: a 2 -D continuous function, f(x, y) Digital image: a 2 -D discrete function, I(r, c) Origin c ○ r Pixel: picture element Gray level: pixel value (0 – 255) 1 -15

1. 8 Types of Digital Images • Grayscale image • Binary image 1 -16

• Color image Indexed (or palette) color image 1 -17

• Multispectral images 1 -18

• Radio images 1 -19

• Ultrasound images 1 -20

• X-ray image 1 -21

• Gamma-ray images 1 -22

• X-ray transmission computerized tomography (CT) image 1 -23

• Ultraviolet images 1 -24

• Range images 1 -25

• Moire images 1 -26

• Structure light images 1 -27

1 -28

1. 9 Image File Sizes Examples: i) 512 by 512 binary image: ii) 512 by 512 greyscale image: iii) 512 by 512 color image: 1 -29

1. 10 Image Perception -- Limitations of human visual system Simultaneous contrast Optical illusion 1 -30

Overshoot and Undershoot 1 -31