前言

openCV处理的图像最小的位深度都是8，即每个像素的灰度值要用8bit存储，二值化处理的图像也是用8bit来存储每个像素的灰度值(0代表黑色，255代表白色)，为什么不能用0和1表示呢，即每个像素用1bit存储。这样保存的图像占用的存储空间更小，在某些场合下会发挥重大的作用，下面直接上代码，将位深8bit的图像保存为位深1bit图像。

代码实现

将位深8bit的图像Mat img转化为位深1bit图像数据。

int 8Bit2Binary(const cv::Mat img, int line_byte, char * data)

{

int width = img.cols;

int height = img.rows;

size_t line_size = line_byte * 8;

size_t bit_size = line_size * height;

char *p = data; int offset, v; unsigned char temp;

for (int row = height - 1; row >= 0; row--)

{

for (int col = 0; col < width; col++)

{

offset = col % 8;

v = img.data[row * width + col];

temp = 1;

temp = temp << (8 - offset - 1);

if (v == 255)

{

*(p + col / 8) |= temp;

}

else

{

temp = ~temp;

*(p + col / 8) &= temp;

}

}

for (int j = width / 8; j < line_byte; j++)

p[j] = 0;

p = p + line_byte;

}

return 0;

}

将位深8bit的图像保存为位深1bit图像。

int save1BitImage(const cv::Mat img, std::string dst)

{

int width = img.cols;

int height = img.rows;

const int biBitCount = 1;

//颜色表大小，以字节为单位，灰度图像颜色表为256*4字节，彩色图像颜色表大小为0,二值图为2*4

int color_type_num = 2;

int colorTablesize = color_type_num * sizeof(RGBQUAD);

RGBQUAD *pColorTable = new RGBQUAD[color_type_num];

for (int i = 0; i < color_type_num; i++) {

pColorTable[i].rgbBlue = i * 255;

pColorTable[i].rgbRed = i * 255;

pColorTable[i].rgbGreen = i * 255;

pColorTable[i].rgbReserved = 0;

}

//待存储图像数据每行字节数为4的倍数

int line_byte = (width * biBitCount >> 3 + 3) / 4 * 4;

char * p_data = (char *)malloc(line_byte*height);

//统计算法执行时间

double start = static_cast(cv::getTickCount());

8Bit2Binary(img, line_byte, p_data);

//统计算法运行时间

double end = static_cast(cv::getTickCount());

double run_time = (end - start) / cv::getTickFrequency();

std::cout << "Run Time1:" << run_time * 1000 << "ms" << std::endl;

std::ofstream fp(dst.c_str(), std::ios::binary | std::ios::out);

if (!fp.is_open()) {

// cout << "open " << dst << " failed!" << endl;

return -1;

}

//申请位图文件头结构变量，填写文件头信息

BITMAPFILEHEADER fileHead;

fileHead.bfType = 0x4D42; //bmp类型

fileHead.bfSize = sizeof(BITMAPFILEHEADER) + sizeof(BITMAPINFOHEADER)\

+ colorTablesize + line_byte*height; //bfSize是图像文件4个组成部分之和

fileHead.bfReserved1 = 0;

fileHead.bfReserved2 = 0;

fileHead.bfOffBits = 54 + colorTablesize; //bfOffBits是图像文件前3个部分所需空间之和

fp.write((char *)&fileHead, sizeof(BITMAPFILEHEADER)); //写文件头进文件

//申请位图信息头结构变量，填写信息头信息

BITMAPINFOHEADER head;

head.biBitCount = biBitCount;

head.biClrImportant = 0;

head.biClrUsed = 0;

head.biCompression = 0;

head.biHeight = height;

head.biPlanes = 1;

head.biSize = 40;

head.biSizeImage = line_byte*height;

head.biWidth = width;

head.biXPelsPerMeter = 0;

head.biYPelsPerMeter = 0;

//写位图信息头进内存

fp.write((char *)&head, sizeof(BITMAPINFOHEADER));

//颜色表，写入文件

fp.write((char *)pColorTable, sizeof(RGBQUAD)*color_type_num);

//写位图数据进文件pBmpBuf

fp.write((char *)p_data, height*line_byte);

fp.close();

delete[]pColorTable;

delete[]p_data;

return 0;

}

测试效果

//测试8bit转1bit图像

void test_8Bit2OneBit()

{

Mat src = imread(".\\test.bmp", 0);//加载图像

string dst = ".\\result.bmp";//存放生成1位位图的路径

int a;

//统计算法执行时间

double start = static_cast(cv::getTickCount());

a = save1BitImage(src, dst);

//统计算法运行时间

double end = static_cast(cv::getTickCount());

double run_time = (end - start) / cv::getTickFrequency();

std::cout << "Run Time:" << run_time * 1000 << "ms" << std::endl;

system("pause");

}

最后

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