PSNR和SSIM的c++实现

您好！下面是PSNR（峰值信噪比）和SSIM（结构相似性指数）的C++实现示例：

PSNR的C++实现示例：

#include <iostream>
#include <opencv2/opencv.hpp>

double calculatePSNR(const cv::Mat& original, const cv::Mat& compressed) {
    cv::Mat diff;
    cv::absdiff(original, compressed, diff);
    diff.convertTo(diff, CV_32F);
    diff = diff.mul(diff);

    double mse = cv::mean(diff)[0];
    double psnr = 10.0 * log10((255 * 255) / mse);
    return psnr;
}

int main() {
    cv::Mat original = cv::imread("original.png", cv::IMREAD_GRAYSCALE);
    cv::Mat compressed = cv::imread("compressed.png", cv::IMREAD_GRAYSCALE);

    if (original.empty() || compressed.empty()) {
        std::cout << "Failed to load images!" << std::endl;
        return -1;
    }

    double psnr = calculatePSNR(original, compressed);
    std::cout << "PSNR: " << psnr << " dB" << std::endl;

    return 0;
}

请注意，上述示例使用了OpenCV库来处理图像。

SSIM的C++实现示例：

#include <iostream>
#include <opencv2/opencv.hpp>

cv::Scalar calculateSSIM(const cv::Mat& original, const cv::Mat& compressed) {
    const double C1 = 6.5025, C2 = 58.5225;

    cv::Mat originalFloat, compressedFloat;
    original.convertTo(originalFloat, CV_32F);
    compressed.convertTo(compressedFloat, CV_32F);

    cv::Mat originalSquared = originalFloat.mul(originalFloat);
    cv::Mat compressedSquared = compressedFloat.mul(compressedFloat);
    cv::Mat originalCompressed = originalFloat.mul(compressedFloat);

    cv::Mat muOriginal, muCompressed;
    cv::GaussianBlur(originalFloat, muOriginal, cv::Size(11, 11), 1.5);
    cv::GaussianBlur(compressedFloat, muCompressed, cv::Size(11, 11), 1.5);

    cv::Mat muOriginalSquared = muOriginal.mul(muOriginal);
    cv::Mat muCompressedSquared = muCompressed.mul(muCompressed);
    cv::Mat muOriginalCompressed = muOriginal.mul(muCompressed);

    cv::Mat sigmaOriginalSquared, sigmaCompressedSquared, sigmaOriginalCompressed;
    cv::GaussianBlur(originalSquared, sigmaOriginalSquared, cv::Size(11, 11), 1.5);
    sigmaOriginalSquared -= muOriginalSquared;

    cv::GaussianBlur(compressedSquared, sigmaCompressedSquared, cv::Size(11, 11), 1.5);
    sigmaCompressedSquared -= muCompressedSquared;

    cv::GaussianBlur(originalCompressed, sigmaOriginalCompressed, cv::Size(11, 11), 1.5);
    sigmaOriginalCompressed -= muOriginalCompressed;

    cv::Mat ssimMap;
    cv::divide((2 * muOriginalCompressed + C1) * (2 * sigmaOriginalCompressed + C2), (muOriginalSquared + muCompressedSquared + C1) * (sigmaOriginalSquared + sigmaCompressedSquared + C2), ssimMap);

    cv::Scalar ssim = cv::mean(ssimMap);
    return ssim;
}

int main() {
    cv::Mat original = cv::imread("original.png", cv::IMREAD_GRAYSCALE);
    cv::Mat compressed = cv::imread("compressed.png", cv::IMREAD_GRAYSCALE);

    if (original.empty() || compressed.empty()) {
        std::cout << "Failed to load images!" << std::endl;
        return -1;
    }

    cv::Scalar ssim = calculateSSIM(original, compressed);
    std::cout << "SSIM: " << ssim[0] << std::endl;

    return 0;
}

上述示例同样使用了OpenCV库来处理图像。请确保将原始图像和压缩图像的文件路径正确地指定在`imread`函数中。

希望对您有所帮助！如有任何疑问，请随时追问。