IplImage *TheImage; // TheImage=cvLoadImage(dlg->value_pic_path,-1); TheImage=cvLoadImage("E:\\WD_FILE\\ISE_workplace\\0306\\PIC\\image_pga_output_16k_4k.tif",-1); dlg->DrawPicToHDC(TheImage,IDC_STATIC_PIC); cvReleaseImage(&TheImage); return 0;

这段代码用于加载图像并将绘制到名为 `IDC_STATIC_PIC` 的静态控件上。

首先，声明了一个 `IplImage` 指针 `TheImage`。

然后，使用 `cvLoadImage()` 函数加载图像。注释掉的那行是通过 `dlg->value_pic_path` 变量来指定图像路径，而当前使用的是硬编码的路径。

接下来，调用 `dlg->DrawPicToHDC(TheImage, IDC_STATIC_PIC)` 将加载的图像传递给 `DrawPicToHDC` 函数，并指定要显示图像的静态控件的标识符 `IDC_STATIC_PIC`。

最后，使用 `cvReleaseImage(&TheImage)` 释放图像资源。

函数返回 0 表示执行成功。

相关问题

/*** (1). implementing histogram equalization for image enhancement ***/ bool HistogramEqualization( IplImage* pSrcImg, //@pSrcImg : input gray image IplImage*& pDstImg, //@pDstImg : output histogram equalized gray image IplImage*& pSrcHistImg,//@pSrcHistImg: original histogram of the input IplImage*& pDstHistImg)//@pDstHistImg: equalized histogram of the output { if(!pSrcImg) return false; //create two histogram images pSrcHistImg = cvCreateImage(cvSize(256, 256), 8, 1); pDstHistImg = cvCreateImage(cvSize(256, 256), 8, 1); /*** YOUR CODE HERE ***/ //[50pts] return true; }

pDstImg ) //@pDstImg : output equalized gray image
{
if( !pSrcImg || !pDstImg ) //check if input and output images are valid
return false;

if( pSrcImg->nChannels != 1 || pDstImg->nChannels != 1 ) //check if images are grayscale
return false;

int hist[256] = {0}; //initialize histogram array with zeros

//calculate histogram
for( int i = 0; i < pSrcImg->height; i++ )
{
uchar* ptr = (uchar*)(pSrcImg->imageData + i * pSrcImg->widthStep);
for( int j = 0; j < pSrcImg->width; j++ )
{
hist[ptr[j]]++;
}
}

int cumHist[256] = {0}; //initialize cumulative histogram array with zeros
int totalPixels = pSrcImg->width * pSrcImg->height; //calculate total number of pixels in the image
cumHist[0] = hist[0];
for( int i = 1; i < 256; i++ )
{
cumHist[i] = cumHist[i-1] + hist[i]; //calculate cumulative histogram
}

//normalize cumulative histogram
for( int i = 0; i < 256; i++ )
{
cumHist[i] = (int)(((float)cumHist[i] / totalPixels) * 255 + 0.5);
}

//perform histogram equalization
for( int i = 0; i < pSrcImg->height; i++ )
{
uchar* ptrSrc = (uchar*)(pSrcImg->imageData + i * pSrcImg->widthStep);
uchar* ptrDst = (uchar*)(pDstImg->imageData + i * pDstImg->widthStep);
for( int j = 0; j < pSrcImg->width; j++ )
{
ptrDst[j] = cumHist[ptrSrc[j]]; //map pixel values to equalized values
}
}

return true; //return success
}

可以有opencv 使用C++补全下面的函数/*** (1). implementing histogram equalization for image enhancement ***/ bool HistogramEqualization( IplImage* pSrcImg, //@pSrcImg : input gray image IplImage*& pDstImg, //@pDstImg : output histogram equalized gray image IplImage*& pSrcHistImg,//@pSrcHistImg: original histogram of the input IplImage*& pDstHistImg)//@pDstHistImg: equalized histogram of the output { if (!pSrcImg) return false; //create two histogram images pSrcHistImg = cvCreateImage(cvSize(256, 256), 8, 1); pDstHistImg = cvCreateImage(cvSize(256, 256), 8, 1); /*** YOUR CODE HERE ***/ //[50pts] return true; }

pDstImg //@pDstImg : output gray image with equalized histogram ) {

// check if input image is grayscale
if (pSrcImg->nChannels != 1) {
return false;
}

int hist[256] = {0};
int cum_hist[256] = {0};
int max_intensity = 255;
int total_pixels = pSrcImg->width * pSrcImg->height;

// calculate histogram of input image
for (int i = 0; i < pSrcImg->height; i++) {
uchar* row_ptr = (uchar*)(pSrcImg->imageData + i * pSrcImg->widthStep);
for (int j = 0; j < pSrcImg->width; j++) {
hist[row_ptr[j]]++;
}
}

// calculate cumulative histogram
cum_hist[0] = hist[0];
for (int i = 1; i <= max_intensity; i++) {
cum_hist[i] = cum_hist[i-1] + hist[i];
}

// calculate equalized histogram
for (int i = 0; i <= max_intensity; i++) {
cum_hist[i] = round(((float)cum_hist[i] / total_pixels) * max_intensity);
}

// apply equalized histogram to input image to get output image
for (int i = 0; i < pSrcImg->height; i++) {
uchar* src_row_ptr = (uchar*)(pSrcImg->imageData + i * pSrcImg->widthStep);
uchar* dst_row_ptr = (uchar*)(pDstImg->imageData + i * pDstImg->widthStep);
for (int j = 0; j < pSrcImg->width; j++) {
dst_row_ptr[j] = cum_hist[src_row_ptr[j]];
}
}

return true;
}