素描算法（图像处理）
2021-11-2 ~ 2021-11-16
(6)
素描算法介绍
素描算法其实就是几种简单的图像处理算法，对同一张图片进行处理后，产生的一种类似素描的算法。这里简单的描述一下他的原理。
- 彩色图像进行类似直方图均衡化处理，增强图像的对比度，使得图像的轮廓更加分明。
- 将步骤 1 处理后的彩色图像进行灰度处理得到图像 gray。
- 将得到的图像 gray 复制一份得到图像 gray1。
- 将图像 gray 的像素进行取反，得到负片效果。
- 对步骤 4 获得的图像进行高斯滤波处理。这里高斯滤波处理次数不同，最后的效果也不同。处理得到图像 guassian。
- 图像淡化生成素描图像 sketch。
处理的图像效果
图1 原图
图2 素描算法显示
源码
///////////////////////////////////////////////////
// 程序名称：图像处理——素描算法
// 编译环境：Mictosoft Visual Studio 2013, EasyX_20200315(beta)
// 作 者：luoyh <2864292458@qq.com>
// 最后修改：2021-11-2
//
#include<graphics.h>
#include<conio.h>
#include<stdio.h>
#include<cmath>
const double PI = acos(-1.0);
const double delta = 1.5;
const int pic_Dis = 3;
double P[pic_Dis][pic_Dis];
void GetP(); // 获取高斯滤波算子
class Algorithm
{
public:
Algorithm(IMAGE *img, int width, int heigth);
void Histogram(); // 类似直方图均衡化
void Gray(); // 灰度处理
void Film(); // 负片处理
void Blur(); // 高斯模糊化处理
void Sketch(); // 素描算法
private:
IMAGE *pimg;
int WIDTH;
int HEIGHT;
};
Algorithm::Algorithm(IMAGE *img, int width, int height)
{
pimg = img;
WIDTH = width;
HEIGHT = height;
};
void Algorithm::Film()
{
DWORD* pMem = GetImageBuffer(pimg);
for (int i = pimg->getwidth() * pimg->getheight() - 1; i >= 0; i--)
pMem[i] = (~pMem[i]) & 0x00FFFFFF;
}
void Algorithm::Sketch() // 素描
{
IMAGE *gray, *guassian;
Histogram(); // 直方图
Gray(); // 灰度处理
gray = new IMAGE();
guassian = new IMAGE();
*gray = *pimg;
Film(); //底片处理
// 这里需要考虑的是模糊化处理的次数
for (int i = 0; i < 10; i++)
{
Blur(); //模糊算法
}
*guassian = *pimg;
*pimg = *gray;
DWORD* pMem = GetImageBuffer(pimg);
DWORD* Gray = GetImageBuffer(gray);
DWORD* Guassian = GetImageBuffer(guassian);
int R, G, B;
int RR, GG, BB;
for (int i = WIDTH * HEIGHT - 1; i >= 0; i--)
{
R = GetRValue(Gray[i]);
B = GetBValue(Gray[i]);
G = GetGValue(Gray[i]);
RR = GetRValue(Guassian[i]);
BB = GetBValue(Guassian[i]);
GG = GetGValue(Guassian[i]);
int r = min(R + (R*RR) / (255 - RR), 255);
int g = min(G + (G*GG) / (255 - GG), 255);
int b = min(B + (B*BB) / (255 - BB), 255);
pMem[i] = RGB(r, g, b);
}
delete (gray);
delete(guassian);
}
void Algorithm::Histogram() // 类似直方图
{
DWORD* p_data = GetImageBuffer(pimg);
int height = HEIGHT;
int wide = WIDTH;
int pr[256], pg[256], pb[256];
int size = HEIGHT * WIDTH;
for (int p = 0; p <= 255; p++)
{
int nr = 0, ng = 0, nb = 0;
for (int j = 0; j < height; j++)
{
for (int i = 0; i < wide; i++)
{
if (p == GetRValue(p_data[j * wide + i]))
{
nr++;
}
if (p == GetGValue(p_data[j * wide + i]))
{
ng++;
}
if (p == GetBValue(p_data[j * wide + i]))
{
nb++;
}
}
}
pr[p] = nr;
pg[p] = ng;
pb[p] = nb;
}
double sr[256] = { 0 }, sg[256] = { 0 }, sb[256] = { 0 };
double aver = 0;
double aveg = 0;
double aveb = 0;
bool T = true;
bool K = true;
bool P = true;
int numr, numg, numb;
for (int i = 0; i <= 255; i++)
{
if (T)
{
aver += pr[i] / double(size);
sr[i] = aver;
if (aver == 1)
{
numr = i;
T = false;
}
}
if (K)
{
aveg += pg[i] / double(size);
sg[i] = aveg;
if (aveg == 1)
{
numg = i;
K = false;
}
}
if (P)
{
aveb += pb[i] / double(size);
sb[i] = aveb;
if (aveb == 1)
{
numb = i;
P = false;
}
}
}
int ssr[256] = { 0 }, ssg[256] = { 0 }, ssb[256] = { 0 };
int rx = 0, gx = 0, bx = 0;
for (int i = 0; i <= 255; i++)
{
if (i == 0)
{
ssr[i] = 0;
ssg[i] = 0;
ssb[i] = 0;
}
ssr[i] = (int)(255 * sr[i]);
ssg[i] = (int)(255 * sg[i]);
ssb[i] = (int)(255 * sb[i]);
}
int r = 0, g = 0, b = 0;
double myr = 0, myg = 0, myb = 0;
for (int j = 0; j < height; j++)
{
for (int i = 0; i < wide; i++)
{
myr = ssr[GetRValue(p_data[j * wide + i])];
myg = ssg[GetGValue(p_data[j * wide + i])];
myb = ssb[GetBValue(p_data[j * wide + i])];
p_data[j * wide + i] = RGB(myr, myg, myb);
}
}
};
void Algorithm::Gray()
{
DWORD *p = GetImageBuffer(pimg);
COLORREF c;
for (int i = pimg->getwidth() * pimg->getheight() - 1; i >= 0; i--)
{
c = BGR(p[i]);
c = (GetRValue(c) * 299 + GetGValue(c) * 587 + GetBValue(c) * 114 + 500) / 1000;
p[i] = RGB(c, c, c); // 由于是灰度值，无需再执行 BGR 转换
}
}
void Algorithm::Blur()
{
GetP();
BYTE *R;
BYTE *G;
BYTE *B;
int size = HEIGHT * WIDTH;
R = (BYTE*)calloc(size,sizeof(BYTE));
G = (BYTE*)calloc(size, sizeof(BYTE));
B = (BYTE*)calloc(size, sizeof(BYTE));
DWORD* pMem = GetImageBuffer(pimg);
for (int i = 0; i < size; i++)
{
R[i] = GetRValue(pMem[i]);
G[i] = GetGValue(pMem[i]);
B[i] = GetBValue(pMem[i]);
}
for (int i = WIDTH; i < WIDTH * (HEIGHT - 1); i++)
{
if (i % 500 != 0 || (i + 1) % 500 != 0)
{
pMem[i] = RGB(R[i - (WIDTH + 1)] * P[0][0] + R[i - WIDTH] * P[0][1] + R[i - (WIDTH - 1)] * P[0][2] + R[i - 1] * P[1][0] + R[i] * P[1][1] + R[i + 1] * P[1][2] + R[i + (WIDTH - 1)] * P[2][0] + R[i + WIDTH] * P[2][1] + R[i + (WIDTH + 1)] * P[2][2],
G[i - (WIDTH + 1)] * P[0][0] + G[i - WIDTH] * P[0][1] + G[i - (WIDTH - 1)] * P[0][2] + G[i - 1] * P[1][0] + G[i] * P[1][1] + G[i + 1] * P[1][2] + G[i + (WIDTH - 1)] * P[2][0] + G[i + WIDTH] * P[2][1] + G[i + (WIDTH + 1)] * P[2][2],
B[i - (WIDTH + 1)] * P[0][0] + B[i - WIDTH] * P[0][1] + B[i - (WIDTH - 1)] * P[0][2] + B[i - 1] * P[1][0] + B[i] * P[1][1] + B[i + 1] * P[1][2] + B[i + (WIDTH - 1)] * P[2][0] + B[i + WIDTH] * P[2][1] + B[i + (WIDTH + 1)] * P[2][2]);
}
}
free(R);
free(G);
free(B);
R = G = B = NULL;
}
int main()
{
int width = 0;
int height = 0;
IMAGE g_img;
loadimage(&g_img, _T("src.jpg")); // 加载图片
width = g_img.getwidth();
height = g_img.getheight();
initgraph(width, height);
putimage(0, 0, &g_img);
_getch();
Algorithm myA(&g_img, width, height);
myA.Sketch();
putimage(0, 0, &g_img);
_getch();
return 0;
}
void GetP()
{
for (int i = 0; i < pic_Dis; i++)
{
for (int j = 0; j < pic_Dis; j++)
{
int d = (i - 1) * (i - 1) + (j - 1) * (j - 1);
double x = 1 / (2 * PI * delta);
P[i][j] = x * exp(-d / (2 * delta));
}
}
double pn = 0;
for (int i = 0; i < pic_Dis; i++)
{
for (int j = 0; j < pic_Dis; j++)
{
pn += P[i][j];
}
}
for (int i = 0; i < pic_Dis; i++)
{
for (int j = 0; j < pic_Dis; j++)
{
P[i][j] = P[i][j] / pn;
}
}
}
把这个名字修改成你要添加的图片路径就行