-
Notifications
You must be signed in to change notification settings - Fork 0
/
mean_filter.cpp
258 lines (177 loc) · 5.48 KB
/
mean_filter.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
#include <stdio.h>
#include <stdlib.h>
#include "myImageIO.h"
double kernel_mean[3][3] = {{1/9, 1/9, 1/9},
{1/9, 1/9, 1/9},
{1/9, 1/9, 1/9}};
float kernel_laplace1[3][3] = {{1, 1, 1},
{1, -8, 1},
{1, 1, 1}};
float kernel_laplace2[3][3] = {{1, 1, 1},
{1, -4, 1},
{1, 1, 1}};
float kernel_x[3][3] = {{-1, 0, 1},
{-2, 0, 2},
{-1, 0, 1}};
float kernel_y[3][3] = {{1, 0, -1},
{2, 0, -2},
{1, 0, -1}};
void mean_filter(myImageData * in, myImageData *out){
int W = in->getWidth();
int H = in->getHeight();
int C = in->getCH();
const int winsize = 5;
for(int y = 0; y < H; y++){
for(int x = 0; x < W; x++){
double sum = 0;
int cnt = 0;
for(int j = -winsize; j <= winsize; j++){
int yp = y + j;
if(yp < 0) yp = yp + H;
if(yp > H-1) yp = yp - H;
for(int i = -winsize; i <= winsize; i++){
int xp = x + i;
if(xp < 0) xp = xp + W;
if(xp > W-1) xp = xp - W;
double val_in = in->get(xp, yp);
sum = sum + val_in ;
// sum = sum + val_in * kernelx[i+1][j+1];
cnt = cnt + 1;
}
}
double origin = in->get(x,y);
// double val_out = double(origin) + (double(origin)- double(sum));
double mean = double(sum)/double(cnt) ;
// double val_out = double(sum) +127 ;
double val_out = double(mean);
out->set(x, y, val_out);
}
}
}
void detail_enhance(myImageData * in, myImageData *out){
int W = in->getWidth();
int H = in->getHeight();
int C = in->getCH();
const int winsize = 5;
for(int y = 0; y < H; y++){
for(int x = 0; x < W; x++){
double sum = 0;
int cnt = 0;
for(int j = -winsize; j <= winsize; j++){
int yp = y + j;
if(yp < 0) yp = yp + H;
if(yp > H-1) yp = yp - H;
for(int i = -winsize; i <= winsize; i++){
int xp = x + i;
if(xp < 0) xp = xp + W;
if(xp > W-1) xp = xp - W;
double val_in = in->get(xp, yp);
sum = sum + val_in ;
// sum = sum + val_in * kernelx[i+1][j+1];
cnt = cnt + 1;
}
}
double origin = in->get(x,y);
// double val_out = double(origin) + (double(origin)- double(sum));
double mean = double(sum)/double(cnt) ;
// double val_out = double(sum) +127 ;
double val_out = double(origin) + 2*(double(origin) - double(mean));
out->set(x, y, val_out);
}
}
}
void kernel_mean_filter(myImageData * in, myImageData *out){
int W = in->getWidth();
int H = in->getHeight();
int C = in->getCH();
const int winsize = 1;
for(int y = 0; y < H; y++){
for(int x = 0; x < W; x++){
double sum = 0;
for(int j = -winsize; j <= winsize; j++){
int yp = y + j;
if(yp < 0) yp = yp + H;
if(yp > H-1) yp = yp - H;
for(int i = -winsize; i <= winsize; i++){
int xp = x + i;
if(xp < 0) xp = xp + W;
if(xp > W-1) xp = xp - W;
double val_in = in->get(xp, yp);
// sum = sum + val_in * kernel_mean[i+1][j+1];
sum = sum + val_in * kernel_laplace1[i+1][j+1];
}
}
double origin = in->get(x,y);
double mean = double(sum) ;
double val_out = double(mean) +127;
out->set(x, y, val_out);
}
}
}
void detail_enhance_using_kernel(myImageData * in, myImageData *out){
int W = in->getWidth();
int H = in->getHeight();
int C = in->getCH();
const int winsize = 1;
for(int y = 0; y < H; y++){
for(int x = 0; x < W; x++){
double sum = 0;
double cnt =0;
for(int j = -winsize; j <= winsize; j++){
int yp = y + j;
if(yp < 0) yp = yp + H;
if(yp > H-1) yp = yp - H;
for(int i = -winsize; i <= winsize; i++){
int xp = x + i;
if(xp < 0) xp = xp + W;
if(xp > W-1) xp = xp - W;
double val_in = in->get(xp, yp);
// sum = sum + val_in * kernel_mean[i+1][j+1];
sum = sum + val_in * kernel_x[i+1][j+1]*kernel_x[i+1][j+1]*kernel_y[i+1][j+1]*kernel_laplace1[i+1][j+1]*kernel_laplace2[i+1][j+1];
cnt = cnt +1;
}
}
double origin = in->get(x,y);
// double mean = double(sum);
double edge = double(sum);
double val_out = double(origin) + double(edge);
// double val_out = double(sum) +127 ;
// double val_out = double(origin) + 2*(double(origin) - double(mean))+127;
out->set(x, y, val_out);
}
}
}
int main(int argc, char **argv){
// read image data to img1
myImageData * img1 = new myImageData();
img1->read(argv[1]);
int W = img1->getWidth();
int H = img1->getHeight();
// printf("resolution: %d x %d\n", W, H);
// mean result
myImageData *img2 = new myImageData();
img2->init(W, H, 1);
mean_filter(img1, img2);
img2->save("./HW/mean_filter_result");
// detail enhance using mean
myImageData *img3 = new myImageData();
img3->init(W, H, 1);
detail_enhance(img1, img3);
img3->save("./HW/detail_enhance_using _mean_result");
// mean result using kernel
myImageData *img4 = new myImageData();
img4->init(W, H, 1);
kernel_mean_filter(img1, img4);
img4->save("./HW/kernel_mean_filter_results");
// detail enhance result using kernel
myImageData *img5 = new myImageData();
img5->init(W, H, 1);
detail_enhance_using_kernel(img1, img5);
img5->save("./HW/detail_enhance_using _kernel_result");
delete img1;
delete img2;
delete img3;
delete img4;
delete img5;
return 0; // normal termination
}