Digital Image Processing ECE 448: Spring 2014 Lab 5 Digital Image Processing

Agenda for today Part 1: Midterm Exam Grades & Discussion Part 2: Introduction to Lab5 2

Digital Image The digital image is picture information in digital form consisting of pixels. The position of each pixel is specified in terms of an index for the number of columns and another for the number of rows. p(2, 8) = 86 m = 2 n = 8

Image Quality More is better! The image quality mostly depends on 1. Spatial Resolution: The number of pixels in the representation of a digital image. Typically represented as width x height As high as 1600 x 1200, or As low as 320 x 200 100 x 200 25 x 50 Digital: Computer manipulation: Image as a data matrix More is better!

Image Quality Color Depth: The color depth determines how many different colors each pixel can display Bits Per pixel Possible Colors Common Name 1 2 Monochrome 4 CGA 16 EGA 8 256 VGA 65536 XGA, High Color 24 16777216 SVGA, True Color

1-bit 2-bit 4-bit 8-bit 24-bit

8-bit Gray Level Images Each pixel is encoded on a gray scale from 0 – 255, where 0 is black and 255 is white. All numbers in between represent levels of the grayscale

24-bit Color Images Each pixel has three components Red Green Blue Each component is encoded in 8-bits 24 bit Color 8-bits 8-bits 8-bits 24 bit Image

8-bit Indexed Color Images Each pixel value is a color index that points to a color lookup table. Color Map 8-bit indexed color Image

8-bit Indexed Color Images

RGB to Grayscale Conversion Conversion from RGB space to YIQ space required to generate the histogram. Y : luminance channel (represents the light intensity) I : In-space channel Q: Quadrature chrominance channel Both I and Q channels represent color details. Y(m, n) carries grayscale information with most of the signal energy

Grayscale to RGB Conversion The following transformation is used to convert back to RGB space.

Grayscale Histogram A graph to show how many pixels are at each level. The histogram contains information needed for image equalization, where the image pixels are stretched to give a reasonable contrast. Image encoded with 8 bits per pixel, the pixel value ranges from 0 to 255

Histogram Generation for different Image Types For grayscale image: Use the grayscale values to generate the histogram For RGB color image: Convert RGB to YIQ Use Y channel to generate the histogram For indexed color image: Convert the color map from RGB to YIQ

Equalization of the Histogram data Image pixels are stretched to give a reasonable contrast in the equalized image   The accumulative counts can range up to the total number of pixles, so the equalized pixel value can vary from 0 to maximum scale level.

RGB Image Equalization Flow

Original & Equalized Image