7-2

Question 1

spatial domain info (3)

Answer 1

• deals images as is
• value of the pixels of the image change with respect to scene
• directly deals with image matrix

Question 2

spatial domain process

Answer 2

input image matrix -> processing -> output image matirx

Question 3

frequency domain info (2)

Answer 3

• deals the rate of changing/intensified pixel values
• any spatial domain image can be rep. in freq. domain

Question 4

frequency domain process

Answer 4

input image -> frequency distribution -> processing -> inverse transformation -> output image

Question 5

freq. domain transformation

Answer 5

A non-periodic signal (eg image) can be converted from spatial domain to frequency domain using mathematical operators called transformation

Question 6

examples of freq. domain transformation (4)

Answer 6

Fourier Series, Fourier transformation, Laplace transformation, Z-transform

Question 7

what is fourier transform (3)

Answer 7

• is a mathematical formula using integrals
• decomposition of an image (spatially) into a series of its sine and cosine components eg. a1cos(f(t)) + b1sin(f(t))……
• represent an image as a summation of cosine/sine like image

Question 8

Discrete Fourier Transform (DFT) info (3)

Answer 8

• transform is complex
• image in spatial domain consist of discrete intensity value, thus the term DFT.
• DFT is sampled Fourier Transform. does not contain all frequencies forming an image, but only a set of samples which is large enough to fully describe the spatial domain image

Question 9

Inverse Discrete Fourier Transform (IDFT) info

Answer 9

• Reverses the frequency domain image into spatial domain.

Question 10

applications of fourier transform (4)

Answer 10

• image processing for convolution computation
• image compression (e.g JPEG compression)
• Noise removal/reduction -> easier to remove undesirable frequencies in the frequency domain
• Faster operations in the frequency domain than in the spatial domain

Question 11

what is FFT

Answer 11

Fast Fourier Transform, a faster way to calculate DFT

Question 12

Frequency Domain Filter info (2)

Answer 12

• like a mask in convolution
• after converting image to frequency domain, some filters applied in filtering process to perform different kind of processing on an image. processing includes blurring an image, sharpening an image etc.

Question 13

common Frequency Domain Filters (4)

Answer 13

• Ideal high pass filter – ideal for sharpening ie. increases the edge content
• Ideal low pass filter
• Gaussian high pass filter
• Gaussian low pass filter