CSCE4240 - Exam 2

Question 1

histogram algorithm

step 1.

Answer 1

create a one-dimensional array h of size L with initial value of zero

Question 2

histogram algorithm
step 1. create one-dimensional array h of size L with initial value of zero
step 2.

Answer 2

loop through all pixels in the image A

Question 3

histogram algorithm
step 1. create one-dimensional array h of size L with initial value of zero
step 2. loop through all pixels in the image
step 3.

Answer 3

for a pixel value v, increase the value at h(v) by one

Question 4

histogram algorithm
step 1. create one-dimensional array h of size L with initial value of zero
step 2. loop through all pixels in the image
step 3. for a pixel value v, increase the value of h(v) by one
step 4.

Answer 4

continue until all pixels in the image A are visited

Question 5

what is an image histogram

Answer 5

acts as a graphical representation of the tonal distribution in a digital image

Question 6

what is histogram stretching

Answer 6

maps the value of all pixels to a new value that spans the full gray scale range

Question 7

what is histogram equalization

Answer 7

maximize the usage of the full brightness range. maximum contrast is achieved when image histogram is uniform distribution

Question 8

median filter algorithm

Answer 8

sort all the pixels in an increasing order and take the middle value

Question 9

what are sampling rates

Answer 9

rate at which amplitude values are digitized from the original waveform

Question 10

what is sinusoidal basis

Answer 10

use smoothly-varying sinusoidal patters at different frequencies, angles for basis of images - hadamard basis doesn’t capture real image gradients

Question 11

what is magnitude

Answer 11

how much of a certain frequency component is in an image

Question 12

what is phase

Answer 12

where that certain frequency lies

Question 13

butterworts lowpass filter

Answer 13

introduces unwanted artifacts into the result. uses smooth transition

Question 14

JPEG encoding

step 1.

Answer 14

transform RGB to YUV and subsample color

Question 15

JPEG encoding
step 1. transform RGB to YUV and subsample color
step 2.

Answer 15

perform discrete cosine transform on 8x8 image blocks

Question 16

JPEG encoding
step 1. transform RGB to YUV and subsample color
step 2. perform discrete cosine transform on 8x8 image blocks
step 3.

Answer 16

perform quantization

Question 17

JPEG encoding
step 1. transform RGB to YUV and subsample color
step 2. perform discrete cosine transform on 8x8 image blocks
step 3. perform quantization
step 4.

Answer 17

zig-zag ordering and run-length encoding

Question 18

JPEG encoding
step 1. transform RGB to YUV and subsample color
step 2. perform discrete cosine transform on 8x8 image blocks
step 3. perform quantization
step 4. zig-zag ordering and run-length encoding
step 5.

Answer 18

entropy encoding

Question 19

what is quantization

Answer 19

aims at reducing the total number of bits by dividing each entry in the frequency space block by an integer then round

Question 20

wavelet-based image fusion

step 1.

Answer 20

decompose images using wavelet transform

Question 21

wavelet-based image fusion
step 1. decompose images using wavelet transform
step 2.

Answer 21

combine coefficients

1. combine approximation subbing and the average
2. select the maximum among detail subtends and put in the composite

Question 22

wavelet-based image fusion
step 1. decompose images using wavelet transform
step 2. combine coefficients
step 3.

Answer 22

perform inverse wavelet transform on the composite wavelet matrix

Question 23

noise-aware image fusion algorithm

step 1.

Answer 23

decompose images with wavelet transform

Question 24

noise-aware image fusion algorithm
step 1. decompose images with wavelet transform
step 2.

Answer 24

compute the subbing noise variance On

Question 25

noise-aware image fusion algorithm step 1. decompose images with wavelet transform step 2. compute the subbing noise variance step 3.

Answer 25

estimate the threshold (lamda) that separate SIC and NIC

Question 26

noise-aware image fusion algorithm step 1. decompose images with wavelet transform step 2. compute the subbing noise variance step 3. estimate the threshold (lamda) that separate SIC and NIC step 4/5.

Answer 26

4. combine SIC | 5. combine NIC

Question 27

noise-aware image fusion algorithm step 1. decompose images with wavelet transform step 2. compute the subbing noise variance step 3. estimate the threshold (lamda) that separate SIC and NIC step 4/5. combine SIC and combine NIC step 6.

Answer 27

synthesize a fused image from the subbing composite

Question 28

JPEG2000 algorithm | 1.

Answer 28

image tilting

Question 29

JPEG2000 algorithm 1. image tilting 2.

Answer 29

DC-level shifting

Question 30

JPEG2000 algorithm 1. image tilting 2. DC-level shifting 3.

Answer 30

components tranformation

Question 31

``` JPEG2000 algorithm 1. image tilting 2. DC-level shifting 3. components tranformation 4. ```

Answer 31

wavelet transform

Question 32

``` JPEG2000 algorithm 1. image tilting 2. DC-level shifting 3. components tranformation 4. wavelet transform 5. ```

Answer 32

quantization

Question 33

``` JPEG2000 algorithm 1. image tilting 2. DC-level shifting 3. components tranformation 4. wavelet transform 5. quantization 6. ```

Answer 33

coefficient coding

Question 34

Image morphology edge detection | 1.

Answer 34

dilate the original image

Question 35

Image morphology edge detection 1. dilate the original image 2.

Answer 35

subtract the original image from the dilated one

Question 36

looks for particular pattern within the image

Answer 36

hit-and-miss transform

Question 37

delete any such point that has more than one foreground neighbor, as long as doing so does not locally disconnect the region

Answer 37

thinning

Question 38

suppresses the bright details that are smaller than the specified SE

Answer 38

opening

Question 39

suppresses the dark details

Answer 39

closing

Question 40

Chain Code | 1.

Answer 40

find the top-left pixel on the boundary; call P0

Question 41

Chain Code 1. find the top-left pixel on the boundary; call P0 2.

Answer 41

traverse the four neighborhood of the current pixel in the counter-clockwise order

Question 42

Chain Code 1. find the top-left pixel on the boundary; call P0 2.traverse the four neighborhood of the current pixel in the counter-clockwise order 3

Answer 42

stop when current boundary pixel Pk equals to P1 and Pk-1 equals to P0

Question 43

mean shift | 1.

Answer 43

start from an arbitrary point in the distribution

Question 44

mean shift 1. start from an arbitrary point in the distribution 2.

Answer 44

region of interest is a circle centered at this point

Question 45

mean shift 1. start from an arbitrary point in the distribution 2. region of interest is a circle centered at this point 3.

Answer 45

on each iteration, find the center of mass for the ROI

Question 46

mean shift 1. start from an arbitrary point in the distribution 2. region of interest is a circle centered at this point 3. on each iteration, find the center of mass for the ROI 4.

Answer 46

move the circle to this center

Question 47

mean shift 1. start from an arbitrary point in the distribution 2. region of interest is a circle centered at this point 3. on each iteration, find the center of mass for the ROI 4. move the circle to this center 5.

Answer 47

continue the iterations until it convergences

Question 48

hough transform | 1.

Answer 48

discretize parameter space into bins

Question 49

hough transform | 1. discretize parameter space into bins

Answer 49

for each feature point in the image, put a vote in every bin in the parameter space that could have generated this point

Question 50

hough transform 1. discretize parameter space into bins 2. for each feature point in the image, put a vote in every bin in the parameter space that could have generated this point 3

Answer 50

find bins that have the most votes

Question 51

selecting seed without a-priori knowledge

Answer 51

compute the histogram and choose the grey values with the highest peak

Question 52

otsu thresholding method idea

Answer 52

find the threshold that minimizes the weighted within-class variance and maximizes the between class variance

Question 53

otsu thresholding method assumption

Answer 53

the histogram is a binomial distribution and the objects colors are mostly homogeneous