1 Image Basics Hao Jiang Computer Science Department Sept. 4, 2014

Image Formulation  The most common way to obtain an image is from a camera 2

A “Simple” Camera 3 Let’s hold a sensor (a film) in front of the object. Hopefully we will have an image…

A “Simple” Camera 4 Unfortunately, at the same image point, light may come from different source points on an object.

The Pinhole Camera 5

Camera with Lens 6

The Imaging Model 7 lighting Surface property: material, geometry. Camera pose, Optical properties

Images as Surfaces Image can be treated as a 2D function z = f(x, y).

Image Profile 9

Sampling  To “digitize” the continuous image, we need to sample the image first. Sampling on a grid Sampling problem

The image of Barbara

Aliasing due to sampling

fs = 2.5f fs = 1.67f Original signal A new component is added This is denoted as aliasing.

Image Resolution  Sensor: size of the real world scene into a single image pixel.  Image: number of Pixels. 14

Digitization  The samples are continuous and have infinite number of possible values.  The digitization process approximates these values with a fixed number of numbers.  To represent N numbers, we need log 2 N bits.  So, what determines the number of bits we need for an image?

Image as Matrices

Types of Digital Images  Grayscale image  Usually we use 256 levels for each pixel. Thus we need 8bits to represent a pixel (2^8 == 256)  Some images use more bits per pixel, for example MRI images could use 16bits / pixel. A 8bit grayscale Image.

 Binary Image A binary image has only two values (0 or 1). Binary image is quite important in image analysis and object detection applications.

Gay Scale Image as a Stack of Binary Images [ b7 b6 b5 b4 b3 b2 b1 b0] MSBLSB Each bit plane is a binary image.

Dithering  A technique to represent a grayscale image with a binary one. 0  1  2  3  Convert image to 4 levels: I’ = floor(I/64)

Color Image r g b 24 bit image

Color Table Image with 256 colors r g b Clusters of colors It is possible to use much less colors to represent a color image without much degradation.

Gamma Correction  Display device’s brightness is not linearly related to the input. I’ = I    To compensate for the nonlinear distortion we need to raise it to a power again (I’) 1/  = I   for CRT is about 2.2.

Gamma Correction Linearly increasing intensity without gamma correction Linearly increasing intensity with gamma correction

Image File Formats  An image in “ppm” format: P6: (this is a ppm image) Resolution: 512x512 Depth: (8bits per pixel in each channel)

An image contains a header and a bunch of (integer) numbers.

Image Compression and Encoding  Raw image takes a lot of space. Compute the file sizes of a raw image that has resolution 512x512 in true color.  BMP, PPM, TXT  Images can be “compressed” losslessly or lossly  Lossy image format: JPEG  Losslessly compressed image format: PNG  Compression ratio and bit rate 27

Digital Video Frame N-1 Frame 0 time Digital video is digitized version of a 3D function f(x,y,t)