Images of different gray levels

Conclusion 1: for images with more details, the gray level is relatively independent of sensory quality when the image size (N) remains unchanged;

Explanation: If the image details are large and the gray level is reduced, the visual perception is not much different.

Code compilation is relatively casual and performance optimization is not performed. Only observe the effect:

# Define K 1 // grayscale level # define STEP (256/(1 <K) int main () {// char name [50]; iplImage * image = cvLoadImage ("e: \ OpenCV_Image \ airplane.jpg", 0); // IplImage * result = cvCreateImage (cvGetSize (image), 8, 1 ); cvNamedWindow ("source image"); cvNamedWindow (""); cvShowImage ("source image", image); for (int I = 0; I <image-> width; I ++) for (int j = 0; j <image-> height; j ++) {int value = cvGetReal2D (image, I, j); int step = STEP; while (value> step) {step + = STEP;} value = step; cvSetReal2D (image, I, j, value);} cvShowImage ("transform", image ); // sprintf (name, "% s % d % s", "e :\\ OpenCV_Image \ airplane _", K ,". jpg "); // cvSaveImage (name, image); cvWaitKey (); cvReleaseImage (& image); return 0 ;}

The three images are original images, K = 1, 2, 3, 4, 5, 6, and 7, 8 from left to right (level 1 is a binarization image, level 8 is the gray scale of the original image)

Question: How can I evaluate the details of an image at the same resolution...

Images of different gray levels