Question

write in C

Task: Write the imagej macro code to perform Histogram Equalization Your code should perform the following steps: . Find the minimum intensity in the image. Construct a histogram in an array . Construct a cumulative histogram in an array. Construct a lookup table (in an array) that maps old intensity values to new intensity values. Use the round() function! . Use the lookup table to update the image with new values.

Answer 1

// C program to perform histogram equalisation to adjust contrast levels

// All the needed library functions for this program
#include <fcntl.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

// Function to perform histogram equalisation on an image
// Function takes total rows, columns, input file name and output
// file name as parameters
void histogramEqualisation(int cols, int rows,
                       char* input_file_name, char* output_file_name)
{
   // creating image pointer
   unsigned char* image;

   // Declaring 2 arrays for storing histogram values (frequencies) and
   // new gray level values (newly mapped pixel values as per algorithm)
   int hist[256] = { 0 };
   int new_gray_level[256] = { 0 };

   // Declaring other important variables
   int input_file, output_file, col, row, total, curr, i;

   // allocating image array the size equivalent to number of columns
   // of the image to read one row of an image at a time
   image = (unsigned char*)calloc(cols, sizeof(unsigned char));

   // opening input file in Read Only Mode
   input_file = open(input_file_name, O_RDONLY);
   if (input_file < 0) {
       printf("Error opening input file\n");
       exit(1);
   }

   // creating output file that has write and read access
   output_file = creat(output_file_name, 0666);
   if (output_file < 0) {
       printf("Error creating output file\n");
       exit(1);
   }

   // Calculating frequency of occurrence for all pixel values
   for (row = 0; row < rows; row++) {
       // reading a row of image
       read(input_file, &image[0], cols * sizeof(unsigned char));

       // logic for calculating histogram
       for (col = 0; col < cols; col++)
           hist[(int)image[col]]++;
   }

   // calulating total number of pixels
   total = cols * rows;

   curr = 0;

   // calculating cumulative frequency and new gray levels
   for (i = 0; i < 256; i++) {
       // cumulative frequency
       curr += hist[i];

       // calculating new gray level after multiplying by
       // maximum gray count which is 255 and dividing by
       // total number of pixels
       new_gray_level[i] = round((((float)curr) * 255) / total);
   }

   // closing file
   close(input_file);

   // reopening file in Read Only Mode
   input_file = open(input_file_name, O_RDONLY);

   // performing histogram equalisation by mapping new gray levels
   for (row = 0; row < rows; row++) {
       // reading a row of image
       read(input_file, &image[0], cols * sizeof(unsigned char));

       // mapping to new gray level values
       for (col = 0; col < cols; col++)
           image[col] = (unsigned char)new_gray_level[image[col]];

       // reading new gray level mapped row of image
       write(output_file, &image[0], cols * sizeof(unsigned char));
   }

   // freeing dynamically allocated memory
   free(image);

   // closing input and output files
   close(input_file);
   close(output_file);
}

// driver code
int main()
{
   // declaring variables
   char* input_file_name;
   char* output_file_name;
   int cols, rows;

   // defining number of rows and columns in an image
   // here, image size is 512*512
   cols = 512;
   rows = 512;

   // defining input file name (input image name)
   // this boat_512_512 is a raw grayscale image
   input_file_name = "boat_512_512";

   // defining output file name (output image name)
   output_file_name = "boat_512_512_histogram_equalised";

   // calling function to do histogram equalisation
   histogramEqualisation(cols, rows, input_file_name, output_file_name);

   return 0;
}


Results: Boat image before and after Histogram Equalisation (From Left to Right) 90 boat 512 512 boat 512 512 histogram_equalised

Transformation of Histogram before and after Equalisation (From Left to Right) hlstogram_after_equallsation.png 9e histogram_before equalisation.png boo2 histog-.tut" ui 1r2 200 Note that boat image used in the program is a grayscale raw image. ImageJ and GNUplot are used for viewing images and plotting histograms.