OpenCV 之ios Remapping 重映射

目标

本教程向你展示如何使用OpenCV函数 remap 来实现简单重映射.

理论

重映射是什么意思?

把一个图像中一个位置的像素放置到另一个图片指定位置的过程.
为了完成映射过程, 有必要获得一些插值为非整数像素坐标,因为源图像与目标图像的像素坐标不是一一对应的.
我们通过重映射来表达每个像素的位置(x,y)

这里g()是目标图像,f()是源图像,h(x,y)是作用于(x,y)的映射方法函数.

让我们来思考一个快速的例子. 想象一下我们有一个图像 I 我们想满足下面的条件作重映射:

会发生什么? 图像会按照x轴方向发生翻转. 例如, 源图像如下:

看到红色圈关于 x 的位置改变(x轴水平翻转):

通过 OpenCV 的函数 remap 提供一个简单的重映射实现.

代码

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#ifdef __cplusplus
#import <opencv2/opencv.hpp>
#import <opencv2/imgcodecs/ios.h>
#import <opencv2/imgproc.hpp>
#import <opencv2/highgui.hpp>
#import <opencv2/core/operations.hpp>

#import <opencv2/core/core_c.h>
using namespace cv;
using namespace std;

#endif
#import "RemapViewController.h"

@interface RemapViewController ()

@end

@implementation RemapViewController

Mat src, dst;
Mat map_x, map_y;
int ind = 0;
- (void)viewDidLoad {
[super viewDidLoad];

UIImage * src1Image = [UIImage imageNamed:@"dog.jpg"];
src = [self cvMatFromUIImage:src1Image];
UIImageView *imageView;
imageView = [self createImageViewInRect:CGRectMake(0, 100, 150, 150)];
[self.view addSubview:imageView];
imageView.image = [self UIImageFromCVMat:src];
dst.create( src.size(), src.type() );
map_x.create( src.size(), CV_32FC1 );
map_y.create( src.size(), CV_32FC1 );

[self createTimer:1 exeBlock:^{
[self update_map];
remap( src, dst, map_x, map_y, CV_INTER_LINEAR, BORDER_CONSTANT, Scalar(0,0, 0) );
UIImageView *imageView;
imageView = [self createImageViewInRect:CGRectMake(0, 250, 150, 150)];
[self.view addSubview:imageView];
imageView.image = [self UIImageFromCVMat:dst];
}];
}
-(void)update_map{
ind = ind%4;

for( int j = 0; j < src.rows; j++ )
{ for( int i = 0; i < src.cols; i++ )
{
switch( ind )
{
case 0:
if( i > src.cols*0.25 && i < src.cols*0.75 && j > src.rows*0.25 && j < src.rows*0.75 )
{
map_x.at<float>(j,i) = 2*( i - src.cols*0.25 ) + 0.5 ;
map_y.at<float>(j,i) = 2*( j - src.rows*0.25 ) + 0.5 ;
}
else
{ map_x.at<float>(j,i) = 0 ;
map_y.at<float>(j,i) = 0 ;
}
break;
case 1:
map_x.at<float>(j,i) = i ;
map_y.at<float>(j,i) = src.rows - j ;
break;
case 2:
map_x.at<float>(j,i) = src.cols - I ;
map_y.at<float>(j,i) = j ;
break;
case 3:
map_x.at<float>(j,i) = src.cols - I ;
map_y.at<float>(j,i) = src.rows - j ;
break;
} // end of switch
}
}
ind++;
}

#pragma mark - private
//brg
- (cv::Mat)cvMatFromUIImage:(UIImage *)image
{
CGColorSpaceRef colorSpace =CGColorSpaceCreateDeviceRGB();

CGFloat cols = image.size.width;
CGFloat rows = image.size.height;
Mat cvMat(rows, cols, CV_8UC4); // 8 bits per component, 4 channels (color channels + alpha)
CGContextRef contextRef = CGBitmapContextCreate(cvMat.data, // Pointer to data
cols, // Width of bitmap
rows, // Height of bitmap
8, // Bits per component
cvMat.step[0], // Bytes per row
colorSpace, // Colorspace
kCGImageAlphaNoneSkipLast |
kCGBitmapByteOrderDefault); // Bitmap info flags
CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), image.CGImage);
CGContextRelease(contextRef);

Mat dst;
Mat src;
cvtColor(cvMat, dst, COLOR_RGBA2BGRA);
cvtColor(dst, src, COLOR_BGRA2BGR);

return src;
}

-(UIImage *)UIImageFromCVMat:(cv::Mat)cvMat
{
// mat 是brg 而 rgb
Mat src;
NSData *data=nil;
CGBitmapInfo info =kCGImageAlphaNone|kCGBitmapByteOrderDefault;
CGColorSpaceRef colorSpace;
if (cvMat.depth()!=CV_8U) {
Mat result;
cvMat.convertTo(result, CV_8U,255.0);
cvMat = result;
}
if (cvMat.elemSize() == 1) {
colorSpace = CGColorSpaceCreateDeviceGray();
data= [NSData dataWithBytes:cvMat.data length:cvMat.elemSize()*cvMat.total()];
} else if(cvMat.elemSize() == 3){
cvtColor(cvMat, src, COLOR_BGR2RGB);
data= [NSData dataWithBytes:src.data length:src.elemSize()*src.total()];
colorSpace = CGColorSpaceCreateDeviceRGB();
}else if(cvMat.elemSize() == 4){
colorSpace = CGColorSpaceCreateDeviceRGB();
cvtColor(cvMat, src, COLOR_BGRA2RGBA);
data= [NSData dataWithBytes:src.data length:src.elemSize()*src.total()];
info =kCGImageAlphaNoneSkipLast | kCGBitmapByteOrderDefault;
}else{
NSLog(@"[error:] 错误的颜色通道");
return nil;
}
CGDataProviderRef provider = CGDataProviderCreateWithCFData((__bridge CFDataRef)data);
// Creating CGImage from cv::Mat
CGImageRef imageRef = CGImageCreate(cvMat.cols, //width
cvMat.rows, //height
8, //bits per component
8 * cvMat.elemSize(), //bits per pixel
cvMat.step[0], //bytesPerRow
colorSpace, //colorspace
kCGImageAlphaNone|kCGBitmapByteOrderDefault,// bitmap info
provider, //CGDataProviderRef
NULL, //decode
false, //should interpolate
kCGRenderingIntentAbsoluteColorimetric //intent
);
// Getting UIImage from CGImage
UIImage *finalImage = [UIImage imageWithCGImage:imageRef];
CGImageRelease(imageRef);
CGDataProviderRelease(provider);
CGColorSpaceRelease(colorSpace);
return finalImage;
}
@end

说明

1.首先准备程序用到的变量:

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Mat src, dst;
Mat map_x, map_y;
int ind = 0;

2.加载一幅图像:

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UIImage * src1Image = [UIImage imageNamed:@"dog.jpg"];
src = [self cvMatFromUIImage:src1Image];
UIImageView *imageView;
imageView = [self createImageViewInRect:CGRectMake(0, 100, 150, 150)];
[self.view addSubview:imageView];
imageView.image = [self UIImageFromCVMat:src];

3.创建目标图像和两个映射矩阵.( x 和 y )

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dst.create( src.size(), src.type() );
map_x.create( src.size(), CV_32FC1 );
map_y.create( src.size(), CV_32FC1 );

4.建立一个间隔1000毫秒的循环,每次循环执行更新映射矩阵参数并对源图像进行重映射处理(使用 mat_x 和 mat_y),然后把更新后的目标图像显示出来:

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[self createTimer:1 exeBlock:^{
[self update_map];
remap( src, dst, map_x, map_y, CV_INTER_LINEAR, BORDER_CONSTANT, Scalar(0,0, 0) );
UIImageView *imageView;
imageView = [self createImageViewInRect:CGRectMake(0, 250, 150, 150)];
[self.view addSubview:imageView];
imageView.image = [self UIImageFromCVMat:dst];
}];

上面用到的重映射函数 remap. 参数说明: