【发布时间】：2012-05-21 06:16:05
【问题描述】：
我已经为 dft 做了一些预处理，我正在尝试通过 imwrite 保存这张图片。
我的裁剪图像有这个信息
output.type() 5
output.channels() 1
output.depth() 5
但是每次我保存它都会输出黑色。我已经检查了 stackoverflow 的旧现有线程，但似乎都对我不起作用。 例如 OpenCV2.3 imwrite saves black image
我也尝试了很多颜色转换和深度转换，但我不知道为什么它不起作用。
std::vector<int> qualityType;
qualityType.push_back(CV_IMWRITE_JPEG_QUALITY);
qualityType.push_back(90);
Mat out1,out2;
cv::cvtColor(output, out1, CV_GRAY2BGR);
//out1.convertTo(out2,CV_8U,1./256); // i tried this too
cv::imwrite("dft1.jpg",out1,qualityType); // tried even using quality type
imshow 可以很好地显示此图像，只有当我保存它时才会出现问题。
请帮忙
[编辑] 也许我制作的 dft 类有问题，因为每当我使用 dft 函数时，输出只能与 inshow 一起使用，但保存时它不起作用。
CDftRidgeAnalyses::CDftRidgeAnalyses(void)
{
}
CDftRidgeAnalyses::~CDftRidgeAnalyses(void)
{
}
Mat CDftRidgeAnalyses::GetRidgeAnalyses(Mat inpGray)
{
Mat img = inpGray;
int WidthPadded=0,HeightPadded=0;
WidthPadded=img.cols*2;
HeightPadded=img.rows*2;
int M = getOptimalDFTSize( img.rows );
//Create a Gaussian Highpass filter 5% the height of the Fourier transform
double db = 0.05 * HeightPadded;
Mat fft = ForierTransform(img.clone(),HeightPadded,WidthPadded);
Mat ghpf = CreateGaussianHighPassFilter(Size(WidthPadded, HeightPadded), db);
Mat res;
cv::mulSpectrums(fft,ghpf,res,DFT_COMPLEX_OUTPUT);
Mat mag = GetDftToImage(res,img);
int cx = mag.cols/2;
int cy = mag.rows/2;
cv::Mat croped = mag(cv::Rect(0,0,cx, cy));
cv::threshold(mag, mag, 0.019, 1, cv::THRESH_BINARY);
Mat bgr;
cvtColor(mag,bgr,CV_GRAY2RGB);
//imshow("XXX",bgr);
//imshow("croped", croped);
//imshow("img",img);
//
//cv::waitKey();
return croped;
}
Mat CDftRidgeAnalyses::ForierTransform(Mat inpGray,int M,int N)
{
Mat img = inpGray;
int i = img.channels();
Mat padded;
Mat img2;
img.convertTo(img2,CV_64F,1./255);
copyMakeBorder(img2, padded, 0, M - img2.rows, 0, N - img2.cols, BORDER_CONSTANT, Scalar::all(0));
Mat element1 = Mat_<float>(padded);
Mat element2 = Mat::zeros(padded.size(), CV_32F);
Mat planes[] = {element1, element2};
Mat complexImg;
merge(planes, 2, complexImg);
dft(complexImg, complexImg ,0, img.rows);
//printMat(complexImg);
return complexImg;
}
double CDftRidgeAnalyses::pixelDistance(double u, double v)
{
return cv::sqrt(u*u + v*v);
}
double CDftRidgeAnalyses::gaussianCoeff(double u, double v, double d0)
{
double d = pixelDistance(u, v);
return 1.0 - cv::exp((-d*d) / (2*d0*d0));
}
cv::Mat CDftRidgeAnalyses::CreateGaussianHighPassFilter(cv::Size size, double cutoffInPixels)
{
Mat ghpf(size, CV_32F);
cv::Point center2((size.width*0.80), size.width/2);
//cv::Point center2(0,0);
for(int u = 0; u < ghpf.rows; u++)
{
for(int v = 0; v < ghpf.cols; v++)
{
ghpf.at<float>(u, v) = gaussianCoeff(u - center2.x, v - center2.y, cutoffInPixels);
}
}
Mat bmp;
int channels = ghpf.channels();
int type = ghpf.type();
int depth = ghpf.depth();
cv::cvtColor(ghpf,bmp,CV_GRAY2RGB);
cv::cvtColor(ghpf,bmp,CV_GRAY2BGRA);
//imshow("XXX",bmp);
int cx = ghpf.cols/2;
int cy = ghpf.rows/2;
Mat tmp;
int iExactright = (size.width*0.59);
int iExactbottom = (size.height*0.86);
//full Mat q0(ghpf, Rect(69,10,400,290));
// Mat whiteq(ghpf, Rect(0,390,270,330));
int iMainleft=0, iMainright=0;
int iMainBottom=0,iMainTop=0;
Mat Quad;
Mat ql(ghpf, Rect(190,0,270,330));
/** Make the rectangle on middle default filter with respect to top right angle**/
iMainleft=(size.width*0.111);
iMainright=(size.width*0.402);
iMainTop=(size.height*0.484);
iMainBottom = (size.height*0.155);
Quad = ghpf(Rect(iMainleft,iMainTop,iMainright+6,iMainBottom));
Mat qTopRight(ghpf, Rect(iExactright,0, iMainright+6, iMainBottom));
Quad.copyTo(qTopRight);
/** Make the rectangle on middle default filter with respect to top left angle**/
iMainright=(size.width*0.402);
Quad = ghpf(Rect(300,iMainTop,300,iMainBottom));
Mat qTopLeft(ghpf, Rect(0,0, 300, iMainBottom));
Quad.copyTo(qTopLeft);
/** Make the rectangle on middle default filter with respect to bottom left angle**/
iMainTop = iMainTop-iMainBottom;
iExactbottom = size.height - iMainBottom;
Quad = ghpf(Rect(300,iMainTop,300,iMainBottom));
Mat qBottomLeft(ghpf, Rect(0,iExactbottom, 300, iMainBottom));
Quad.copyTo(qBottomLeft);
/** Make the rectangle on middle default filter with respect to bottom right angle**/
iMainleft=(size.width*0.111);
iMainright=(size.width*0.402);
Quad = ghpf(Rect(iMainleft,iMainTop,iMainright+6,iMainBottom));
Mat qBottomRight(ghpf, Rect(iExactright,iExactbottom, iMainright+6, iMainBottom));
Quad.copyTo(qBottomRight);
// remove middle rectangle [ circle ]
iMainright=(size.width*0.402);
Quad = ghpf(Rect(0,iMainTop+iMainTop,size.width,iMainBottom+iMainBottom-130));
Mat qMiddle(ghpf,Rect(0,iMainTop+150,size.width,iMainBottom+iMainBottom-130));
Quad.copyTo(qMiddle);
qMiddle =ghpf(Rect(0,iMainTop-10,size.width,iMainBottom+iMainBottom-130));
Quad.copyTo(qMiddle);
normalize(ghpf, ghpf, 0, 1, CV_MINMAX);
/*Mat x;
cv::resize(ghpf,x,cv::Size(400,700));
imshow("fftXhighpass2", x);*/
Filter = ghpf;
Mat padded;
copyMakeBorder(ghpf, padded, 0, size.height - ghpf.rows, 0, size.width - ghpf.cols, BORDER_CONSTANT, Scalar::all(0));
Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
Mat complexImg;
merge(planes, 2, complexImg);
return complexImg;
}
Mat CDftRidgeAnalyses::GetDftToImage(Mat res,Mat orgImage)
{
idft(res,res,DFT_COMPLEX_OUTPUT,orgImage.rows);
Mat padded;
copyMakeBorder(orgImage, padded, 0,orgImage.rows, 0, orgImage.cols, BORDER_CONSTANT, Scalar::all(0));
Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
split(res, planes);
magnitude(planes[0], planes[1], planes[0]);
Mat mag = planes[0];
mag += Scalar::all(1);
// log(mag, mag);
// crop the spectrum, if it has an odd number of rows or columns
mag = mag(Rect(0, 0, mag.cols & -2, mag.rows & -2));
normalize(mag, mag, 1, 0, CV_MINMAX);
return mag;
}
我要保存的输出来自
Mat org = imread("4.png",CV_LOAD_IMAGE_GRAYSCALE);
Mat re;
resize(org,re,cv::Size(311,519));
Mat xyz = CDftRidgeAnalyses::GetRidgeAnalyses(re);
cv::imwrite("dft1.jpg",xyz);
这里的矩阵 xyz 有这些值
output.type() 5
output.channels() 1
output.depth() 5
我希望你们现在可以更好地帮助我......也许在从复杂过滤器转换后我失去了一些分数？？？？
【问题讨论】：
-
初步说明：您正在尝试在示例代码中编写 bmp 文件，同时提供 jpeg 参数。你先检查了吗？
-
我什至在没有使用参数的情况下用 bmp 检查它，以前我用 jpg 检查但对它们都不起作用。是的，我错误地忘记了删除质量类型，但这不是问题。当我保存它时，图像仍然是黑色的。
-
如果您包含 .type()、.depth() 的整数值所代表的内容，将会很有帮助。它是浮点图像（值 0-1）。如果是这样，您是否在保存之前应用了适当的缩放比例？
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我确实尝试了与您完全相同的代码，只是我正在从磁盘读取文件，然后用上面的示例编写它。它就像一个魅力（opencv 2.4，mac os）。您应该再次检查您的输入图像（类型、值...）。
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你的深度是 16 位浮点数。 imwrite 需要 8bit，除了 jpeg2000 文件。
标签： c++ opencv matrix save depth