/simple-image-processing

This research paper contains computer codes for different problems on how to fix the intensity level of image and the implementation of thresholding function for converting images to a binary scale as well as making enhancement using different methods like log transformation, power-law transformation and reconstruction of image using bit planes

Primary LanguageMATLAB

simple-image-processing

This research paper contains computer codes for different problems on how to fix the intensity level of image and the implementation of a thresholding function for converting images to a binary scale as well as making enhancement using different methods like log transformation, power-law transformation and determine which method is more effective and in which cases, in the end, reconstruction of the image by using the bit planes method to compress images. The tool used in this paper is MATLAB desktop version “MATLAB R2022b”.

Implementation and algorithm

Explanation of each case with mathematical calculation step by step with example of each algorithm.

Example_1a

Reduce the number of intensity levels in an image from 256 to 2, in integer powers of 2. Apply your program to Figure “Im_1”

matrix_1

0 5 0 1
6 7 2 0
0 0 4 1 
        Algorithm If number is >= 1, then number is =1, else number = 0

Output_matrix

0 1 0 1
1 1 1 0
0 0 1 1

Figure1_A

Example_1b

Use at least four thresholding values in the interval [0, L-1], and produce the corresponding binary images matrix_1

0 5 0 1
6 7 2 0
0 0 4 1 
    Threshold = 4
    Algorithm If number is >= Threshold, then number is = 0” white”, if number is < Threshold then, 
    number = 255” black”

Output_matrix

255 0 255 255
0 0 255 255
255 0 0 255

Figure1_B

Example_1c

Reversing the intensity levels of Figure “Im_2” to produce the equivalent of a photographic negative. matrix_1

216 216 248 255
250 188 167 143
83 111 124 205

Matrix_ones

1 1 1 1
1 1 1 1
1 1 1 1

Matrix_1_double

0.84 0.84 0.97 1
0.98 0.73 0.65 0.56
0.32 0.43 0.48 0.80 
    Algorithm Output_matrix = Matrix_ones – Matrix_1_double

Output_matrix

0.16 0.16 0.03 0
0.02 0.27 0.35 0.44
0.68 0.57 0.52 0.20

Figure1_C

Example_2

Enhance Figure “Im_3” using the log transformation (s=clog(1+r)). Obtain the best visual enhancement according to your judgment. matrix_1

216 216 248 255
250 188 167 143
83 111 124 205

Matrix_1_double

0.84 0.84 0.97 1
0.98 0.73 0.65 0.56
0.32 0.43 0.48 0.80 
    Algorithm Output_matrix =2*log (1+ Matrix_1_double)

Output_matrix

0.52 0.52 0.58 0.60
0.59 0.47 0.43 0.38
0.24 0.31 0.34 0.51

Figure2

Example_3

Enhance Figure “Im_4” using the power-law transformation (s=cr^γ). Obtain the best visual enhancement according to your judgment. matrix_1

216 216 248 255
250 188 167 143
83 111 124 205

Matrix_1_double

0.84 0.84 0.97 1
0.98 0.73 0.65 0.56
0.32 0.43 0.48 0.80 
    Algorithm Output_matrix =2* (Matrix_1_double)y where y=1.8 in this case

Output_matrix

1.46 1.46 1.89 2
1.90 1.13 1.13 0.70
0.25 0.43 0.53 1.33

Figure3

Example_4

Figure4

Example_5

The contribution to the total image appearance by specific bits can be highlighted. Decompose Figure “Im_2” into its bit planes. Then reconstruct the same image by using its upper three planes.

matrix_1

216 216 248 255
250 188 167 143
83 111 124 205

Bin_matrix

11011000 11011000 11111000 11111111
11111010 10111100 10100111 10001111
01010011 01101111 11111000 11001101

MSB

10000000 10000000 10000000 10000000
10000000 10000000 10000000 10000000
00000000 00000000 10000000 10000000

Bin_7

01000000 01000000 01000000 01000000
01000000 00000000 00000000 00000000
01000000 01000000 01000000 01000000

Bin_6

00000000 00000000 00100000 00100000
00100000 00100000 00100000 00000000
00000000 00100000 00100000 00000000

Bin_5

00010000 00010000 00010000 00010000
00010000 00010000 00000000 00000000
00010000 00000000 00010000 00000000

Bin_4

00001000 00001000 00001000 00001000
00001000 00001000 00000000 00001000
00000000 00001000 00000000 00001000

Bin_3

00000000 00000000 00000000 00000100
00000000 00000100 00000100 00000100
00000000 00000100 00000000 00000100

Bin_2

00000000 00000000 00000000 00000010
00000010 00000000 00000010 00000010
00000010 00000010 00000000 00000000

Bin_1

00000000 00000000 00000000 00000001
00000000 00000000 00000001 00000001
00000001 00000001 00000000 00000001 
    Output_matrix= MSB+Bin_7+Bin_6
11000000 11000000 11100000 11100000
11100000 10100000 10100000 10000000
01000000 01100000 11100000 10100000

Figure5