Step by Step solution about How to resolve the algorithm Bitmap/Histogram step by step in the C programming language

The provided C code is designed to perform image processing tasks, specifically histogram computation and median thresholding. Here's a step-by-step explanation of the code:

1. Type Definitions:

   • histogram_t and histogram are typedefs used to represent a histogram. A histogram is an array of 256 elements, where each element counts the occurrences of a specific intensity value in an image.

2. Image Structure:

   • The code assumes the existence of an image structure, which likely represents an image in memory with attributes such as width, height, and pixel data.
   • grayimage is a pointer to an image structure that stores grayscale images.

3. GET_LUM Macro:

   • This macro is used to access the luminance (or intensity) value of a pixel at the specified coordinates (X and Y) within the image pointed to by IMG.

4. get_histogram Function:

   • This function takes a grayscale image (im) as input and returns a histogram representing the distribution of intensity values in the image.
   • It initializes a histogram t with 256 elements, all set to 0.
   • It iterates through all the pixels in the input image and increments the corresponding element in t based on the pixel's luminance value.
   • The result is a histogram where each element represents the number of pixels with that specific intensity value in the image.

5. luminance histogram_median Function:

   • This function takes a histogram h as input and computes the median luminance value using a binary search approach.
   • It iterates until the left and right cumulative sums of the histogram become equal.
   • The returned value is the median luminance value, which divides the histogram into two equal halves.

6. Usage Example (the main Function):

   • This function demonstrates the functionality of the previous functions by reading an image file, converting it to grayscale, computing its histogram, finding the median luminance, and applying a threshold to the image based on the median.
   • If a pixel's luminance is less than the median, it's set to black; otherwise, it's set to white.
   • The processed image is then output as a PPM file.

In summary, this code performs image processing tasks including histogram computation and median thresholding to create a binary image where pixels below the median luminance are black and those above are white.

typedef unsigned int histogram_t;
typedef histogram_t *histogram;

#define GET_LUM(IMG, X, Y) ( (IMG)->buf[ (Y) * (IMG)->width + (X)][0] )

histogram get_histogram(grayimage im);
luminance histogram_median(histogram h);


histogram get_histogram(grayimage im)
{
   histogram t;
   unsigned int x, y;
   
   if ( im == NULL ) return NULL;
   t = malloc( sizeof(histogram_t)*256 );
   memset(t, 0, sizeof(histogram_t)*256 );
   if (t!=NULL)
   {
       for(x=0; x < im->width; x++ )
       {
         for(y=0; y < im->height; y++ )
         {
            t[ GET_LUM(im, x, y) ]++;
         }
       }
   }
   return t;
}


luminance histogram_median(histogram h)
{
    luminance From, To;
    unsigned int Left, Right;
    
    From = 0; To = (1 << (8*sizeof(luminance)))-1;
    Left = h[From]; Right = h[To];
    
    while( From != To )
    {
       if ( Left < Right )
       {
          From++; Left += h[From];
       } else {
          To--; Right += h[To];
       }
    }
    return From;
}


#include <stdio.h>
#include <stdlib.h>
#include "imglib.h"

/* usage example */

#define BLACK 0,0,0
#define WHITE 255,255,255

int main(int argc, char **argv)
{
    image color_img;
    grayimage g_img;
    histogram h;
    luminance T;
    unsigned int x, y;
    
    if ( argc < 2 )
    {
       fprintf(stderr, "histogram FILE\n");
       exit(1);
    }
    color_img = read_image(argv[1]);
    if ( color_img == NULL ) exit(1);
    g_img = tograyscale(color_img);
    h = get_histogram(g_img);
    if ( h != NULL )
    {
          T = histogram_median(h);
          
          for(x=0; x < g_img->width; x++)
          {
            for(y=0; y < g_img->height; y++)
            {
               if ( GET_LUM(g_img,x,y) < T )
               {
                   put_pixel_unsafe(color_img, x, y, BLACK);
               } else {
                   put_pixel_unsafe(color_img, x, y, WHITE);
               }
            }
          }
          output_ppm(stdout, color_img);
          /* print_jpg(color_img, 90); */
          free(h);
    }
       
    free_img((image)g_img);
    free_img(color_img);
}