OpenCV / C ++-将图像转换为双精度向量以进行FFT（快速傅立叶变换）

Question

I'm trying to compute the FFT (Fast Fourier Transform) of an image to use the frequencies to determine whether or not the image is blurry.

I need to use a custom FFT algorithm that we already have in our codebase. The FFT algorithm requires a standard 1D vector of doubles or ints . I need a way to read in an image and then convert it to a vector of doubles so that I can compute the FFT of the image.

I have tried the following:

cv::Mat inputImage = cv::imread("testImage.png");
cv::Mat fImage; 

inputImage.convertTo(fImage, CV_32F); 
std::vector<double> actualImage = fImage.clone();

However, I am getting the error:

OpenCV Error: Assertion failed (channels() == CV_MAT_CN(dtype)) in copyTo,

Any ideas to how I can achieve this?

Answer 1

CV_32F means float , not double . You should use CV_64F instead.

You also need to specify the number of channels. This example is for 1 channel image (grayscale), and probably what you need:

// Load the image
cv::Mat inputImage = cv::imread("testImage.png");
// Convert to single channel (grayscale)
cv::cvtColor(inputImage, inputImage, cv::COLOR_BGR2GRAY);

// Or directly load as grayscale    
// cv::Mat inputImage = cv::imread("testImage.png", cv::IMREAD_GRAYSCALE);

// Convert to double
cv::Mat fImage; 
inputImage.convertTo(fImage, CV_64F); 

// Initialize the vector with the image content
std::vector<double> actualImage(fImage.begin<double>(), fImage.end<double>());

For 3 channels you can do:

cv::Mat inputImage = cv::imread("testImage.png");
cv::Mat fImage; 

inputImage.convertTo(fImage, CV_64F); 
fImage = fImage.reshape(1); // You need to reshape to single channel
std::vector<double> actualImage(fImage.begin<double>(), fImage.end<double>());