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April 7, 2014 12:16
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Basic implementations of gaussian blur, scaling image using linear interpolation, and shrinking an image by simple resampling
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#include <iostream> | |
#include <math.h> | |
#include <stdio.h> | |
#include <stdlib.h> | |
#include <string.h> | |
#include <unistd.h> | |
#include <opencv2/imgproc/imgproc.hpp> | |
#include <opencv2/highgui/highgui.hpp> | |
#define WINDOW_TITLE "Gaussian Blur" | |
#define IMAGE "chugach-mtns.jpg" | |
#define SIGMA 1.0 | |
using namespace cv; | |
using namespace std; | |
int main(int argc, char *argv[]) | |
{ | |
namedWindow(WINDOW_TITLE, WINDOW_AUTOSIZE); | |
Mat src = imread(IMAGE); | |
Mat blur = Mat::zeros(src.rows, src.cols, CV_8UC3); | |
double kernel[3][3]; | |
double sum = 0; | |
double sigFactor = 1.0 / (2.0 * M_PI * SIGMA * SIGMA); | |
// Calculate 3x3 kernel given sigma | |
for (int x = 0; x < 3; ++x) { | |
int xdist = abs(x - 1); | |
int xdistsq = xdist * xdist; | |
for (int y = 0; y < 3; ++y) { | |
int ydist = abs(y - 1); | |
int ydistsq = ydist * ydist; | |
kernel[x][y] = sigFactor * exp(-((xdist + ydistsq) / (2.0 * SIGMA * SIGMA))); | |
sum += kernel[x][y]; | |
} | |
} | |
// Normalize Sigma | |
for (int x = 0; x < 3; ++x) { | |
for (int y = 0; y < 3; ++y) { | |
kernel[x][y] = kernel[x][y] / sum; | |
} | |
} | |
// Log Kernel for Sanity Check | |
for (int x = 0; x < 3; ++x) { | |
printf("%f %f %f\n", kernel[x][0], kernel[x][1], kernel[x][2]); | |
} | |
// Apply kernel | |
for (int i = 1; i < blur.rows - 1; ++i) { | |
for (int j = 1; j < blur.cols - 1; ++j) { | |
Vec3b p0 = src.at<Vec3b>(i - 1, j - 1); | |
Vec3b p1 = src.at<Vec3b>(i - 1, j); | |
Vec3b p2 = src.at<uchar>(i - 1, j + 1); | |
Vec3b p3 = src.at<Vec3b>(i, j - 1); | |
Vec3b p4 = src.at<Vec3b>(i, j); | |
Vec3b p5 = src.at<Vec3b>(i, j + 1); | |
Vec3b p6 = src.at<Vec3b>(i + 1, j - 1); | |
Vec3b p7 = src.at<Vec3b>(i + 1, j); | |
Vec3b p8 = src.at<Vec3b>(i + 1, j + 1); | |
double r = | |
p0[0] * kernel[0][0] + p1[0] * kernel[0][1] + p2[0] * kernel[0][2] + | |
p3[0] * kernel[1][0] + p4[0] * kernel[1][1] + p5[0] * kernel[1][2] + | |
p6[0] * kernel[2][0] + p7[0] * kernel[2][1] + p8[0] * kernel[2][2]; | |
double g = | |
p0[1] * kernel[0][0] + p1[1] * kernel[0][1] + p2[1] * kernel[0][2] + | |
p3[1] * kernel[1][0] + p4[1] * kernel[1][1] + p5[1] * kernel[1][2] + | |
p6[1] * kernel[2][0] + p7[1] * kernel[2][1] + p8[1] * kernel[2][2]; | |
double b = | |
p0[2] * kernel[0][0] + p1[2] * kernel[0][1] + p2[2] * kernel[0][2] + | |
p3[2] * kernel[1][0] + p4[2] * kernel[1][1] + p5[2] * kernel[1][2] + | |
p6[2] * kernel[2][0] + p7[2] * kernel[2][1] + p8[2] * kernel[2][2]; | |
Vec3b q0; | |
q0[0] = r; | |
q0[1] = g; | |
q0[2] = b; | |
blur.at<Vec3b>(i, j) = q0; | |
} | |
} | |
imshow(WINDOW_TITLE, blur); | |
waitKey(0); | |
} |
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#include <iostream> | |
#include <stdio.h> | |
#include <stdlib.h> | |
#include <string.h> | |
#include <unistd.h> | |
#include <opencv2/imgproc/imgproc.hpp> | |
#include <opencv2/highgui/highgui.hpp> | |
#define WINDOW_TITLE "2x Scale Down" | |
#define IMAGE "chugach-mtns.jpg" | |
using namespace cv; | |
using namespace std; | |
int main(int argc, char *argv[]) | |
{ | |
namedWindow(WINDOW_TITLE, WINDOW_AUTOSIZE); | |
Mat src = imread(IMAGE); | |
Mat scaled = Mat::zeros(src.rows / 2, src.cols / 2, CV_8UC3); | |
for (int i = 0; i < scaled.rows; ++i) { | |
for (int j = 0; j < scaled.cols; ++j) { | |
scaled.at<Vec3b>(i, j) = src.at<Vec3b>(i * 2, j * 2); | |
} | |
} | |
imshow(WINDOW_TITLE, scaled); | |
waitKey(0); | |
} |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
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#include <iostream> | |
#include <stdio.h> | |
#include <stdlib.h> | |
#include <string.h> | |
#include <unistd.h> | |
#include <opencv2/imgproc/imgproc.hpp> | |
#include <opencv2/highgui/highgui.hpp> | |
#define WINDOW_TITLE "2x Scale Up" | |
#define IMAGE "chugach-mtns.jpg" | |
using namespace cv; | |
using namespace std; | |
int main(int argc, char *argv[]) | |
{ | |
namedWindow(WINDOW_TITLE, WINDOW_AUTOSIZE); | |
Mat src = imread(IMAGE); | |
Mat scaled = Mat::zeros(src.rows * 2, src.cols * 2, CV_8UC3); | |
Vec3b p0; | |
Vec3b p1; | |
Vec3b pInterpolated; | |
for (int i = 0; i < src.rows; ++i) { | |
for (int j = 0; j < src.cols; ++j) { | |
scaled.at<Vec3b>(i * 2, j * 2) = src.at<Vec3b>(i, j); | |
if (i + 1 == src.rows) { | |
scaled.at<Vec3b>(i * 2 + 1, j * 2) = src.at<Vec3b>(i, j); | |
} else { | |
p0 = src.at<Vec3b>(i, j); | |
p1 = src.at<Vec3b>(i + 1, j); | |
pInterpolated.val[0] = p0.val[0] + (p1.val[0] - p0.val[0]) * 0.5; | |
pInterpolated.val[1] = p0.val[1] + (p1.val[1] - p0.val[1]) * 0.5; | |
pInterpolated.val[2] = p0.val[2] + (p1.val[2] - p0.val[2]) * 0.5; | |
scaled.at<Vec3b>(i * 2 + 1, j * 2) = pInterpolated; | |
} | |
if (j + 1 == src.cols) { | |
scaled.at<Vec3b>(i * 2, j * 2 + 1) = src.at<Vec3b>(i, j); | |
} else { | |
p0 = src.at<Vec3b>(i, j); | |
p1 = src.at<Vec3b>(i, j + 1); | |
pInterpolated.val[0] = p0.val[0] + (p1.val[0] - p0.val[0]) * 0.5; | |
pInterpolated.val[1] = p0.val[1] + (p1.val[1] - p0.val[1]) * 0.5; | |
pInterpolated.val[2] = p0.val[2] + (p1.val[2] - p0.val[2]) * 0.5; | |
scaled.at<Vec3b>(i * 2, j * 2 + 1) = pInterpolated; | |
} | |
if (i + 1 == src.rows || j + 1 == src.cols) { | |
scaled.at<Vec3b>(i * 2 + 1, j * 2 + 1) = src.at<Vec3b>(i, j); | |
} else { | |
p0 = src.at<Vec3b>(i, j); | |
p1 = src.at<Vec3b>(i + 1, j + 1); | |
pInterpolated.val[0] = p0.val[0] + (p1.val[0] - p0.val[0]) * 0.5; | |
pInterpolated.val[1] = p0.val[1] + (p1.val[1] - p0.val[1]) * 0.5; | |
pInterpolated.val[2] = p0.val[2] + (p1.val[2] - p0.val[2]) * 0.5; | |
scaled.at<Vec3b>(i * 2 + 1, j * 2 + 1) = pInterpolated; | |
} | |
} | |
} | |
imshow(WINDOW_TITLE, scaled); | |
waitKey(0); | |
} |
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