Matrix subtraction normalization

asked 2016-02-15 09:16:10 -0500

chr0x gravatar image

updated 2016-02-15 13:58:11 -0500

Hello everyone.

Recently i had to implement an algorithm to subtract an image from this same image blurred. I first tried to:

Mat img = imread("some_image");
GaussianBlur(img, blurred, Size(7, 7), 0, 0);
Mat result = img - blurred;

But my output (result) was displayed as an black image.

So I found this normalization steps to solve the problem:

result_pixel = (pixel_image - pixel_blurred_image) / 2 + 127 ; for each pixel on image:

void sub(Mat & src, Mat & src2, Mat & result ) {

        for (int i = 0; i < src.cols ; i++) {
                for (int j = 0; j < src.rows; j++) {

                        int px1  = int(src.at<uchar>(j, i));
                        int px2 = int(src2.at<uchar>(j, i));
                        int px   = ( (px1 - px2 ) / 2) + 127;

                        result.at<uchar>(j, i) = px;

                }
        }
}

This kinda of normalization seems trivial to me. So I was wondering, doesn't Opencv already provides any option to apply this normalization automatically?

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Comments

Yes, your image seems it is blank because the noise has very low values, so you cannot see something with your eyes, you need a normalization. I would suggest you to transform images in CV_32F first then do the subtraction and then apply the normalize function on the result to make it more visible

thdrksdfthmn gravatar imagethdrksdfthmn ( 2016-02-15 09:34:22 -0500 )edit

1) you have a buffer overflow: for (int i = 0; i <= src.cols ; i++) must be < , not <= same for rows 2) you only subtract half of px2, your code does not implement the formula above

berak gravatar imageberak ( 2016-02-15 10:07:05 -0500 )edit

ty @berak . updated.

chr0x gravatar imagechr0x ( 2016-02-15 14:02:01 -0500 )edit
1

There are several ways to do it. Like thdrksdfthmn said, the normalize function. If you know the specific numbers to scale and add, you can use convertTo()

Tetragramm gravatar imageTetragramm ( 2016-02-15 18:05:31 -0500 )edit