用chatgpt 生成的 测试了比较卡
for (int y = 0; y < enlargedHeight; y++) {
for (int x = 0; x < enlargedWidth; x++) {
// 计算原始图像中对应的浮点坐标
float originalX = (float)x / (float)enlargedWidth * (float)originalWidth;
float originalY = (float)y / (float)enlargedHeight * (float)originalHeight;
// 进行双三次线性插值计算
QRgb interpolatedPixel = bicubicInterpolation(*img1, originalX, originalY);
// 将计算得到的像素值赋给新图像
newImg->setPixel(x, y, interpolatedPixel);
}
}
// 原始图像大小
const int originalWidth = 32;
const int originalHeight = 24;
// 放大后的图像大小
const int enlargedWidth = 640;
const int enlargedHeight = 480;
// 双三次线性插值函数
QRgb bicubicInterpolation(const QImage& image, float x, float y) {
// 计算四个最近的像素点的坐标
int x1 = qFloor(x);
int y1 = qFloor(y);
int x2 = x1 + 1;
int y2 = y1 + 1;
// 计算插值权重
float dx = x - x1;
float dy = y - y1;
// 获取四个最近的像素点的颜色值
QRgb p11 = image.pixel(x1, y1);
QRgb p12 = image.pixel(x1, y2);
QRgb p21 = image.pixel(x2, y1);
QRgb p22 = image.pixel(x2, y2);
// 对四个像素点进行双三次线性插值计算
float r = qRed(p11) * (1 - dx) * (1 - dy) + qRed(p21) * dx * (1 - dy) + qRed(p12) * (1 - dx) * dy + qRed(p22) * dx * dy;
float g = qGreen(p11) * (1 - dx) * (1 - dy) + qGreen(p21) * dx * (1 - dy) + qGreen(p12) * (1 - dx) * dy + qGreen(p22) * dx * dy;
float b = qBlue(p11) * (1 - dx) * (1 - dy) + qBlue(p21) * dx * (1 - dy) + qBlue(p12) * (1 - dx) * dy + qBlue(p22) * dx * dy;
return qRgb(r, g, b);
}标签:qt,int,QRgb,float,线性插值,dx,dy,三次 From: https://www.cnblogs.com/zhaocundang/p/17948042