Qt图像处理技术二:对QImage图片简单滤镜(暖色,冷色,反色,老照片,灰度)
列举单色滤镜
1.暖色
2.冷色
3.反色
4.老照片
5.灰度
github代码(持续更新)
期待你的小星星
github:https://github.com/dependon/simple-image-filter //qt美颜滤镜
Bound函数,防止越界
int Bound(int range_left, int data, int range_right)
{
int index = data;
if (data > range_right) {
index = range_right;
} else if (data < range_left) {
index = range_left;
}
return index;
}
暖色滤镜
原理如下:
这里红绿越高,颜色越暖,蓝色越高,图片色彩越冷,所以算法为红色和绿色按固定数值增加,蓝色不变。
red=red+30;
green=green+30;
QImage warnImage(const QImage &img, int index)
{
QImage imgCopy;
if (img.format() != QImage::Format_RGB888) {
imgCopy = QImage(img).convertToFormat(QImage::Format_RGB888);
} else {
imgCopy = QImage(img);
}
uint8_t *rgb = imgCopy.bits();
if (nullptr == rgb) {
return QImage();
}
QColor frontColor;
int size = img.width() * img.height();
for (int i = 0; i < size ; i++) {
int r = rgb[i * 3] + index;
int g = rgb[i * 3 + 1] + index;
int b = rgb[i * 3 + 2] ;
rgb[i * 3] = r > 255 ? 255 : r;
rgb[i * 3 + 1] = g > 255 ? 255 : g;
rgb[i * 3 + 2] = b > 255 ? 255 : b;
}
return imgCopy;
}
冷色滤镜
原理如下:
这里红绿越高,颜色越暖,蓝色越高,图片色彩越冷,所以算法为红色和绿色不变,蓝色增加30。
blue=blue+30
QImage coolImage(const QImage &img, int index)
{
QImage imgCopy;
if (img.format() != QImage::Format_RGB888) {
imgCopy = QImage(img).convertToFormat(QImage::Format_RGB888);
} else {
imgCopy = QImage(img);
}
uint8_t *rgb = imgCopy.bits();
if (nullptr == rgb) {
return QImage();
}
QColor frontColor;
int size = img.width() * img.height();
for (int i = 0; i < size ; i++) {
int r = rgb[i * 3] ;
int g = rgb[i * 3 + 1] ;
int b = rgb[i * 3 + 2] + index;
rgb[i * 3] = r > 255 ? 255 : r;
rgb[i * 3 + 1] = g > 255 ? 255 : g;
rgb[i * 3 + 2] = b > 255 ? 255 : b;
}
return imgCopy;
}
灰度滤镜
原理如下:
任何颜色都有红、绿、蓝三原色组成,假如原来某点的颜色为RGB(R,G,B),那么,我们可以通过下面几种方法,将其转换为灰度:
1.浮点算法:Gray = R0.3 + G0.59 + B0.11
2.整数方法:Gray = (R299+G587+B114)/1000
3.移位方法:Gray =(R28+G151+B*77)>> 8
4.平均值法:Gray = (R+G+B)/3
5.仅取绿色:Gray = G
通过以上任何一种方法求得Gray后,将原来的RGB(r,g,b)中的r,g,b统一用Gray替换,形成新的颜色RGB(Gray,Gray,Gray),用它替换原来的RGB(r,g,b)就是灰度图了。
这里采用平均值算法和整数算法
//方案1
QImage GreyScale(const QImage &img)
{
QImage imgCopy;
if (img.format() != QImage::Format_RGB888) {
imgCopy = QImage(img).convertToFormat(QImage::Format_RGB888);
} else {
imgCopy = QImage(img);
}
uint8_t *rgb = imgCopy.bits();
int size = img.width() * img.height();
for (int i = 0; i < size ; i++) {
int average = (rgb[i * 3] * 299 + rgb[i * 3 + 1] * 587 + rgb[i * 3 + 1] * 114 + 500) / 1000;
rgb[i * 3] = average;
rgb[i * 3 + 1] = average;
rgb[i * 3 + 2] = average;
}
return imgCopy;
}
//方案2
QImage QImageAPI::GrayScaleImage(const QImage &img)
{
QImage imgCopy;
if (img.format() != QImage::Format_RGB888) {
imgCopy = QImage(img).convertToFormat(QImage::Format_RGB888);
} else {
imgCopy = QImage(img);
}
uint8_t *rgb = imgCopy.bits();
if (nullptr == rgb) {
return QImage();
}
QColor frontColor;
int size = img.width() * img.height();
for (int i = 0; i < size ; i++) {
int average = (rgb[i * 3] + rgb[i * 3 + 1] + rgb[i * 3 + 2]) / 3;
rgb[i * 3] = average > 255 ? 255 : average;
rgb[i * 3 + 1] = average > 255 ? 255 : average;
rgb[i * 3 + 2] = average > 255 ? 255 : average;
}
return imgCopy;
}
老照片滤镜
原理如下:
该点red值 =0.393x该点red值+0.769x该点green值+0.189x该点blue值
该点green值 =0.349x该点red值+0.686x该点green值+0.168x该点blue值
该点blue值 =0.272x该点red值+0.534x该点green值+0.131x该点blue值
如果遇到超过255的情况,取最大值255
QImage oldImage(const QImage &img)
{
QImage imgCopy;
if (img.format() != QImage::Format_RGB888) {
imgCopy = QImage(img).convertToFormat(QImage::Format_RGB888);
} else {
imgCopy = QImage(img);
}
uint8_t *rgb = imgCopy.bits();
if (nullptr == rgb) {
return QImage();
} int size = img.width() * img.height();
for (int i = 0; i < size ; i++) {
float r = 0.393 * rgb[i * 3] + 0.769 * rgb[i * 3 + 1] + 0.189 * rgb[i * 3 + 2];
float g = 0.349 * rgb[i * 3] + 0.686 * rgb[i * 3 + 1] + 0.168 * rgb[i * 3 + 2];
float b = 0.272 * rgb[i * 3] + 0.534 * rgb[i * 3 + 1] + 0.131 * rgb[i * 3 + 2];
r = Bound(0, r, 255);
g = Bound(0, g, 255);
b = Bound(0, b, 255);
rgb[i * 3] = r;
rgb[i * 3 + 1] = g ;
rgb[i * 3 + 2] = b ;
}
return imgCopy;
}
反色滤镜
原理如下:
每个点的rgb色都变成
该点red值=255-该点red值;
该点green值=255-该点green值;
该点blue值=255-该点blue值;
QImage QImageAPI::InverseColorImage(const QImage &img)
{
QImage imgCopy;
if (img.format() != QImage::Format_RGB888) {
imgCopy = QImage(img).convertToFormat(QImage::Format_RGB888);
} else {
imgCopy = QImage(img);
}
uint8_t *rgb = imgCopy.bits();
if (nullptr == rgb) {
return QImage();
} int size = img.width() * img.height();
for (int i = 0; i < size ; i++) {
rgb[i * 3] = 255 - rgb[i * 3] ;
rgb[i * 3 + 1] = 255 - rgb[i * 3 + 1] ;
rgb[i * 3 + 2] = 255 - rgb[i * 3 + 2] ;
}
return imgCopy;
}