OpenCV之图像处理(五) 图像操作

Vec3b对应三通道的顺序是blue、green、red的uchar类型数据。
Vec3f对应三通道的float类型数据
把CV_8UC1(uchar)转换到CV32F1实现： src.convertTo(dst, CV_32F);

vs代码

#include "../common/common.hpp"

void main1_5(int argc, char ** argv)
{
    Mat src = imread(getCVImagesPath("images/test1_3.png"), IMREAD_COLOR);
    namedWindow("input", CV_WINDOW_AUTOSIZE);
    imshow("input", src);

    Mat gray;
    cvtColor(src, gray, COLOR_BGR2GRAY);
    imshow("output1", gray);
    Mat gray_cha;
    bitwise_not(gray, gray_cha);//颜色值取反，同下面算法一致，这个是通过位操作 与或非 实现的
    imshow("output2", gray_cha);
    int height = gray.rows;
    int width = gray.cols;
    for (int row = 0; row < height; row++)
    {
        for (int col = 0; col < width; col++)
        {
            int pixel = gray.at<uchar>(row, col);//读取图像中 row,col 位置的像素(颜色数据由单通道组成)，所以 <> 中用uchar，只返回的是一个uchar值
            gray.at<uchar>(row, col) = 255 - pixel;//颜色值取反，灰度图的单通道也是一个字节大小，所以值在0-255之间
        }
    }
    imshow("output3", gray);

    Mat dst_cha;
    bitwise_not(src, dst_cha);//颜色值取反，同下面算法一致
    imshow("output4", dst_cha);
    Mat dst;
    dst.create(src.size(), src.type());
    height = src.rows;
    width = src.cols;
    int nc = src.channels();

    Mat convert;
    src.convertTo(convert, CV_32F);//把CV_8UC1(uchar)转换到CV32F1(float), Vec3b对应三通道的顺序是blue、green、red的uchar类型数据。Vec3f对应三通道的float类型数据

    for (int row = 0; row < height; row++)
    {
        for (int col = 0; col < width; col++)
        {
            int b = src.at<Vec3b>(row, col)[0];//读取图像中 row,col 位置的像素(颜色数据由三通道组成)，src是三通道的RGB，所以 <> 传的是Vec3b，返回的是长度3的uchar数组
            int g = src.at<Vec3b>(row, col)[1];
            int r = src.at<Vec3b>(row, col)[2];
            float f_b = convert.at<Vec3f>(row, col)[0];//Vec3f
            float f_g = convert.at<Vec3f>(row, col)[1];
            float f_r = convert.at<Vec3f>(row, col)[2];
            dst.at<Vec3b>(row, col)[0] = 255 - b;//颜色值取反，若分别将 b g r 通道颜色设为0，图片整体颜色为 偏黄、偏绯红、偏青 色
            dst.at<Vec3b>(row, col)[1] = 255 - g;
            dst.at<Vec3b>(row, col)[2] = 255 - r;

            gray.at<uchar>(row, col) = min(b, min(g, r));//随意设置的灰度图，取max图像会比取min亮
        }
    }
    imshow("output5", dst);
    imshow("output6", gray);

    waitKey(0);
}

android代码

@BindView(R.id.iv_opencv1_5_input) ImageView mInputIv;
@BindView(R.id.iv_opencv1_5_output1) ImageView mGrayIv;
@BindView(R.id.iv_opencv1_5_output2) ImageView mGrayFan1Iv;
@BindView(R.id.iv_opencv1_5_output3) ImageView mGrayFan2Iv;
@BindView(R.id.iv_opencv1_5_output4) ImageView mRgbFan1Iv;
@BindView(R.id.iv_opencv1_5_output5) ImageView mRgbFan2Iv;
@BindView(R.id.iv_opencv1_5_output6) ImageView mGrayMinIv;
@BindView(R.id.iv_opencv1_5_output7) ImageView mConvertIv;
private Bitmap mInputBmp;
private Bitmap mGrayBmp;
private Bitmap mGrayFan1Bmp;
private Bitmap mGrayFan2Bmp;
private Bitmap mRgbFan1Bmp;
private Bitmap mRgbFan2Bmp;
private Bitmap mGrayMinBmp;
private Bitmap mConvertBmp;
private Mat mInputMat = new Mat();
private Mat mGrayMat = new Mat();
private Mat mGrayFan1Mat = new Mat();
private Mat mGrayFan2Mat;
private Mat mRgbFan1Mat = new Mat();
private Mat mRgbFan2Mat;
private Mat mGrayMinMat;
private Mat mConvertMat = new Mat();

@Override
protected void onCreate(Bundle savedInstanceState) {
    super.onCreate(savedInstanceState);
    setContentView(R.layout.activity_cv1_5);
    mUnbinder = ButterKnife.bind(this);

    //input
    mInputBmp = CV310Utils.getBitmapFromAssets(this, "opencv/test1_3.png");
    mInputIv.setImageBitmap(mInputBmp);
    initBitmaps(mInputBmp);

    //gray
    Utils.bitmapToMat(mInputBmp, mInputMat);
    Imgproc.cvtColor(mInputMat, mGrayMat, Imgproc.COLOR_BGR2GRAY);
    Utils.matToBitmap(mGrayMat, mGrayBmp);
    mGrayIv.setImageBitmap(mGrayBmp);

    //gray fan1
    long start = System.currentTimeMillis();
    Core.bitwise_not(mGrayMat, mGrayFan1Mat);//颜色值取反，同下面算法一致，这个是通过位操作 与或非 实现的
    LogUtils.d("mydebug---", "gray fan1 : "+(System.currentTimeMillis()-start));//0毫秒。。
    Utils.matToBitmap(mGrayFan1Mat, mGrayFan1Bmp);
    mGrayFan1Iv.setImageBitmap(mGrayFan1Bmp);

    //gray fan2
    mGrayFan2Mat = new Mat(mGrayMat.size(), mGrayMat.type());
    int height = mGrayMat.rows();
    int width = mGrayMat.cols();
    start = System.currentTimeMillis();
    for (int row = 0; row < height; row++) {
        for (int col = 0; col < width; col++) {
            byte pixel[] = new byte[1];//由于是单通道的uchar，这里只能用byte，不能用int
            mGrayMat.get(row, col, pixel);//读取图像中 row,col 位置的像素(颜色数据由单通道组成)，所以只需要读一个值
            pixel[0] = (byte) (255 - CV310Utils.byte2unsignedchar(pixel[0]));//颜色值取反，灰度图的单通道也是一个字节大小，所以值在0-255之间
            mGrayFan2Mat.put(row, col, pixel);
        }
    }
    LogUtils.d("mydebug---", "gray fan2 : "+(System.currentTimeMillis()-start));//1200毫秒
    Utils.matToBitmap(mGrayFan2Mat, mGrayFan2Bmp);
    mGrayFan2Iv.setImageBitmap(mGrayFan2Bmp);

    //Rgb fan1
    start = System.currentTimeMillis();
    Core.bitwise_not(mInputMat, mRgbFan1Mat);
    LogUtils.d("mydebug---", "Rgb fan1 : "+(System.currentTimeMillis()-start));//4毫秒。。
    Utils.matToBitmap(mRgbFan1Mat, mRgbFan1Bmp);
    mRgbFan1Iv.setImageBitmap(mRgbFan1Bmp);

    //Rgb fan2
    mRgbFan2Mat = new Mat(mInputMat.size(), mInputMat.type());
    mGrayMinMat = new Mat(mGrayMat.size(), mGrayMat.type());
    height = mInputMat.rows();
    width = mInputMat.cols();
    //convert
    mInputMat.convertTo(mConvertMat, CvType.CV_32F);//把CV_8UC1(uchar)转换到CV32F1(float), Vec3b对应三通道的顺序是blue、green、red的uchar类型数据。Vec3f对应三通道的float类型数据
    start = System.currentTimeMillis();
    for (int row = 0; row < height; row++) {
        for (int col = 0; col < width; col++) {
            byte rgba[] = new byte[4];//这里是 rgba ，alpha 对 mInputMat 图像会起作用
            mInputMat.get(row, col, rgba);//读取图像中 row,col 位置的像素(颜色数据由四通道RGBA组成)，返回的是长度4的uchar数组
            byte r = rgba[0];
            byte g = rgba[1];
            byte b = rgba[2];
            rgba[0] = (byte) (255 - CV310Utils.byte2unsignedchar(rgba[0]));//颜色值取反
            rgba[1] = (byte) (255 - CV310Utils.byte2unsignedchar(rgba[1]));
            rgba[2] = (byte) (255 - CV310Utils.byte2unsignedchar(rgba[2]));
            mRgbFan2Mat.put(row, col, rgba);

            //gray min
            byte pixel[] = new byte[1];
            pixel[0] = (byte) Math.min(CV310Utils.byte2unsignedchar(r), Math.min(CV310Utils.byte2unsignedchar(g), CV310Utils.byte2unsignedchar(b)));//要用unsigned char比较
            mGrayMinMat.put(row, col, pixel);//随意设置的灰度图，取max图像会比取min亮

            float f_rgba[] = new float[4];
            mConvertMat.get(row, col, f_rgba);
            f_rgba[2] = 0;//2是b，若分别将 b g r 通道颜色设为0，图片整体颜色为 偏黄、偏绯红、偏青 色
            mConvertMat.put(row, col, f_rgba);
        }
    }
    LogUtils.d("mydebug---", "Rgb fan2 : "+(System.currentTimeMillis()-start));//1500毫秒  全部写完后 耗时将近4秒
    Utils.matToBitmap(mRgbFan2Mat, mRgbFan2Bmp);
    mRgbFan2Iv.setImageBitmap(mRgbFan2Bmp);
    Utils.matToBitmap(mGrayMinMat, mGrayMinBmp);
    mGrayMinIv.setImageBitmap(mGrayMinBmp);
    //convert
    Mat mat = new Mat();
    mConvertMat.convertTo(mat, CvType.CV_8UC1);
    Utils.matToBitmap(mat, mConvertBmp);//src.type() == CV_8UC1 || src.type() == CV_8UC3 || src.type() == CV_8UC4   matToBitmap只支持这几种type转换，所以需要把CV_32F再转成CV_8UC1
    mConvertIv.setImageBitmap(mConvertBmp);
}

/*初始化bitmap*/
private void initBitmaps(Bitmap bmp){
    mGrayBmp = Bitmap.createBitmap(bmp.getWidth(), bmp.getHeight(), Bitmap.Config.RGB_565);
    mGrayFan1Bmp = Bitmap.createBitmap(bmp.getWidth(), bmp.getHeight(), Bitmap.Config.RGB_565);
    mGrayFan2Bmp = Bitmap.createBitmap(bmp.getWidth(), bmp.getHeight(), Bitmap.Config.RGB_565);
    mRgbFan1Bmp = Bitmap.createBitmap(bmp.getWidth(), bmp.getHeight(), Bitmap.Config.RGB_565);
    mRgbFan2Bmp = Bitmap.createBitmap(bmp.getWidth(), bmp.getHeight(), Bitmap.Config.RGB_565);
    mGrayMinBmp = Bitmap.createBitmap(bmp.getWidth(), bmp.getHeight(), Bitmap.Config.RGB_565);
    mConvertBmp = Bitmap.createBitmap(bmp.getWidth(), bmp.getHeight(), Bitmap.Config.RGB_565);
}

效果图