: Chapter 1: Introduction 1 Montri Karnjanadecha ac.th/~montri Image Processing

: Chapter 1: Introduction 2 Chapter 1 Introduction

: Chapter 1: Introduction 3 Definition of Image Processing Processing of an image, typically by a computer, to produce another image The computer processing of pictures ( the manipulation of images by computer)

: Chapter 1: Introduction 4 Applications of Image Processing Pictorial databases Graphic design Medical imaging Object recognition Picture enhancement Microscopy

: Chapter 1: Introduction 5 Digital Image Processing System Ima ge digiti zer Input image storage Comp uter Cons ole Output image storage Progra m library Ima ge recor der

: Chapter 1: Introduction 6 Image Shape An image is usually defined as rectangular grids of pixels Image(1..M, 1..N), Image (10,5)

: Chapter 1: Introduction 7 Color Standards A pixel color is represented as a point in 3-D space. Axis may be labeled as independent colors such as R, G, B or may use other independent indicators such as Hue, lightness, saturation. RBG, HSV, HSL are the most popular.

: Chapter 1: Introduction 8 RGB RGB (Red green blue) –For CRT display (TV, computer monitor) –Additive combination of r g and b

: Chapter 1: Introduction 9 HSV HSV (Hue Saturation Value) Hue is effectively a measure of the wavelength of the main color. It has a value between (0-360 o, Red = 0 o, Green=120 o and Blue=240 o.) Hue can be calculated from RGB values as follows: Rh = R - min (R, G, B) Gh = G - min (R, G, B) Bh = B - min (R, G, B) At least on of these values is 0. Hue value is in between.

: Chapter 1: Introduction 10 HSV For example if Rh = 0 Hue angle = (240xBh + 120xGh ) / (Bh + Gh) If two are zero, then hue is the angle corresponding to the third non-zero color. If three are zero, then there is no color hue. The monitor will display a gray level (between black and white).

: Chapter 1: Introduction 11 Saturation Saturation is the amount of pure hue in the final color If Saturation = 0, final color is without hue ( white light only) If Saturation = 255, no white light in final color Saturation = (max(R,G,B) - min (R,G,B)) / max(R,G,B)

: Chapter 1: Introduction 12 Value Value (brightness) is a measure of the intensity of the brightest component and given by Value = max(R,G,B)

: Chapter 1: Introduction 13 The HSV Model

: Chapter 1: Introduction 14 HSV Example Given R=100, G=200, B= 40, convert this RGB color model to HSV. Rh = min(100,200,40) = 60 G h = min (100,200,40) = 160 B h = 40 - min (100,200,40) = 0 H = (60* *(120*256/360))/(60+160)

: Chapter 1: Introduction 15 HSV Example (Continued) Saturation = (max(R,G,B) - min (R,G,B)) / max(R,G,B) = (max(100,200,40)-min(100,200,40))/ max(100,200,40) = (200-40)/200 = 0.8 = 80% Saturation = 80*256/100 = 204 Value = max(100,200,40) = 200 = 200*100/256 = 78%

: Chapter 1: Introduction 16

: Chapter 1: Introduction 17 HLS HLS (Hue Lightness Saturation) Similar to HSV except that the hue angle start at Blue = 0 o, and the model is double cone with a lightness axis going from L=0 (black) to L=1 (white) For HLS, hue is calculated the same way as for HSV model except Blue = 0 and lightness and saturation are given by: Lightness = (max(R,G,B) - min(R,G,B))/2 (max+min)/(max-min) if L <= 0.5 Saturation = (max-min)/(2-max-min) otherwise

: Chapter 1: Introduction 18 HLS

: Chapter 1: Introduction 19 CMY & CMYK CMY (Cyan Magenta Yellow) เป็นระบบสีที่ พัฒนาขึ้นมาใช้สำหรับการพิมพ์ภาพสีโดยมีสีหลัก คือสี Cyan Magenta และ Yellow ซึ่งเรียกว่า Subtractive primaries Color ( สีแดง เขียวและน้ำ เงิน เรียกว่า Additive primaries Color) ระบบสี แบบ CMY สามารถหาได้โดยการนำเอาสีในระบบ RGB ลบกับสีขาวดังนี้คือ

: Chapter 1: Introduction 20 CMY & CMYK ระบบสี CMY จะนำไปใช้สำหรับการพิมพ์ภาพสีแต่ ยังไม่ดีเท่าที่ควรเนื่องจากไม่ยังไม่สามารถสร้างสี ดำได้อย่างถูกต้อง ดังนั้นจึงมีการใช้ระบบ CMYK แทนโดย K แทนสีดำ

: Chapter 1: Introduction 21 The Human Vision Better than any camera yet developed Eye has 2 classes of discrete light receptors; Cones and rods 6-7 million cones, sensitive to bright light >= 75 Million rods, sensitive to light intensity but not color eye color perceptions

: Chapter 1: Introduction 22 Color Additive Problem with CRT