Bitmap/Histogram: Difference between revisions
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<lang c>typedef unsigned int histogram_t; |
<lang c>typedef unsigned int histogram_t; |
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typedef histogram_t *histogram; |
typedef histogram_t *histogram; |
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#define GET_LUM(IMG, X, Y) ( (IMG)->buf[ (Y) * (IMG)->width + (X)][0] ) |
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histogram get_histogram(grayimage im) |
histogram get_histogram(grayimage im); |
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luminance histogram_median(histogram h);</lang> |
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<lang c>histogram get_histogram(grayimage im) |
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{ |
{ |
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histogram t; |
histogram t; |
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<lang c>#include <stdio.h> |
<lang c>#include <stdio.h> |
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#include <stdlib.h> |
#include <stdlib.h> |
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#include "imglib.h" |
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/* usage example */ |
/* usage example */ |
Revision as of 21:21, 23 February 2009
You are encouraged to solve this task according to the task description, using any language you may know.
Extend the basic bitmap storage defined on this page to support dealing with image histograms. The image histogram contains for each luminance the count of image pixels having this luminance. Choosing a histogram representation take care about the data type used for the counts. It must have range of at least 0..NxM, where N is the image width and M is the image height.
Test task
Histogram is useful for many image processing operations. As an example, use it to convert an image into black and white art. The method works as follows:
- Convert image to grayscale;
- Compute the histogram
- Find the median of. The median is defined as the luminance such that the image has an approximately equal number of pixels with lesser and greater luminance.
- Replace each pixel of luminance lesser than the median to black, and others to white.
Use read/write ppm file, and grayscale image solutions.
Ada
Histogram of an image: <lang ada> type Pixel_Count is mod 2**64; type Histogram is array (Luminance) of Pixel_Count;
function Get_Histogram (Picture : Grayscale_Image) return Histogram is
Result : Histogram := (others => 0);
begin
for I in Picture'Range (1) loop for J in Picture'Range (2) loop declare Count : Pixel_Count renames Result (Picture (I, J)); begin Count := Count + 1; end; end loop; end loop; return Result;
end Get_Histogram; </lang> Median of a histogram: <lang ada> function Median (H : Histogram) return Luminance is
From : Luminance := Luminance'First; To : Luminance := Luminance'Last; Left : Pixel_Count := H (From); Right : Pixel_Count := H (To);
begin
while From /= To loop if Left < Right then From := From + 1; Left := Left + H (From); else To := To - 1; Right := Right + H (To); end if; end loop; return From;
end Median; </lang> Conversion of an image to black and white art: <lang ada>
F1, F2 : File_Type;
begin
Open (F1, In_File, "city.ppm"); declare X : Image := Get_PPM (F1); Y : Grayscale_Image := Grayscale (X); T : Luminance := Median (Get_Histogram (Y)); begin Close (F1); Create (F2, Out_File, "city_art.ppm"); for I in Y'Range (1) loop for J in Y'Range (2) loop if Y (I, J) < T then X (I, J) := Black; else X (I, J) := White; end if; end loop; end loop; Put_PPM (F2, X); end; Close (F2);
</lang>
C
<lang c>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);</lang>
<lang c>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;
}</lang>
The given histogram must be freed with a simple free(histogram).
<lang c>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;
}</lang>
An example of usage is the following code.
<lang c>#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);
} </lang>
Which reads from the file specified from the command line and outputs to the standard out the PPM B/W version of the input image. The input image can be of any format handled by ImageMagick (see Read image file through a pipe)
Forth
: histogram ( array gmp -- ) over 256 cells erase dup bdim * over bdata + swap bdata do 1 over i c@ cells + +! loop drop ;
Fortran
Note: luminance range is hard-encoded and is from 0 to 255. This could be enhanced.
<lang fortran>module RCImageProcess
use RCImageBasic implicit none
contains
subroutine get_histogram(img, histogram) type(scimage), intent(in) :: img integer, dimension(0:255), intent(out) :: histogram integer :: i
histogram = 0 do i = 0,255 histogram(i) = sum(img%channel, img%channel == i) end do end subroutine get_histogram
function histogram_median(histogram) integer, dimension(0:255), intent(in) :: histogram integer :: histogram_median integer :: from, to, left, right
from = 0 to = 255 left = histogram(from) right = histogram(to) do while ( from /= to ) if ( left < right ) then from = from + 1 left = left + histogram(from) else to = to - 1 right = right + histogram(to) end if end do histogram_median = from end function histogram_median
end module RCImageProcess</lang>
Example:
<lang fortran>program BasicImageTests
use RCImageBasic use RCImageIO use RCImageProcess
implicit none
type(rgbimage) :: animage type(scimage) :: gray integer, dimension(0:255) :: histo integer :: ml
open(unit=10, file='lenna.ppm', action='read', status='old') call read_ppm(10, animage) close(10)
call init_img(gray) ! or ! call alloc_img(gray, animage%width, animage%height)
gray = animage
call get_histogram(gray, histo) ml = histogram_median(histo) where ( gray%channel >= ml ) animage%red = 255 animage%green = 255 animage%blue = 255 elsewhere animage%red = 0 animage%green = 0 animage%blue = 0 end where
open(unit=10, file='elaborated.ppm', action='write') call output_ppm(10, animage) close(10)
call free_img(animage) call free_img(gray)
end program BasicImageTests</lang>
Vedit macro language
The input image is in edit buffer pointed by numeric register #15. On return, #30 points to buffer containing histogram data. The histogram data is given as ASCII decimal values, one value per line.
:HISTOGRAM: #30 = Buf_Free // #30 = buffer to store histogram data for (#9=0; #9<256; #9++) { Out_Reg(21) TC(#9) Out_Reg(Clear) // @21 = intensity value to be counted Buf_Switch(#15) // switch to image buffer #8 = Search(@21, CASE+BEGIN+ALL+NOERR) // count intensity values Buf_Switch(#30) // switch to histogram buffer Num_Ins(#8, FILL) // store count } Return