Median filter: Difference between revisions
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{{task|
The median filter takes in the neighbourhood the median color (see [[wp:Median filter|Median filter]])
''(to test the function below, you can use these [[Read_ppm_file|input]] and [[Write_ppm_file|output]] solutions)''
=={{header|Action!}}==
{{libheader|Action! Bitmap tools}}
{{libheader|Action! Tool Kit}}
<syntaxhighlight lang="action!">INCLUDE "H6:LOADPPM5.ACT"
INCLUDE "D2:SORT.ACT" ;from the Action! Tool Kit
DEFINE HISTSIZE="256"
PROC PutBigPixel(INT x,y BYTE col)
IF x>=0 AND x<=79 AND y>=0 AND y<=47 THEN
y==LSH 2
col==RSH 4
IF col<0 THEN col=0
ELSEIF col>15 THEN col=15 FI
Color=col
Plot(x,y)
DrawTo(x,y+3)
FI
RETURN
PROC DrawImage(GrayImage POINTER image INT x,y)
INT i,j
BYTE c
FOR j=0 TO image.gh-1
DO
FOR i=0 TO image.gw-1
DO
c=GetGrayPixel(image,i,j)
PutBigPixel(x+i,y+j,c)
OD
OD
RETURN
INT FUNC Clamp(INT x,min,max)
IF x<min THEN
RETURN (min)
ELSEIF x>max THEN
RETURN (max)
FI
RETURN (x)
BYTE FUNC Median(BYTE ARRAY a BYTE len)
SortB(a,len,0)
len==RSH 1
RETURN (a(len))
PROC Median3x3(GrayImage POINTER src,dst)
INT x,y,i,j,ii,jj,index,sum
BYTE ARRAY arr(9)
BYTE c
FOR j=0 TO src.gh-1
DO
FOR i=0 TO src.gw-1
DO
sum=0 index=0
FOR jj=-1 TO 1
DO
y=Clamp(j+jj,0,src.gh-1)
FOR ii=-1 TO 1
DO
x=Clamp(i+ii,0,src.gw-1)
c=GetGrayPixel(src,x,y)
arr(index)=c
index==+1
OD
OD
c=Median(arr,9)
SetGrayPixel(dst,i,j,c)
OD
OD
RETURN
PROC Main()
BYTE CH=$02FC ;Internal hardware value for last key pressed
BYTE ARRAY dataIn(900),dataOut(900)
GrayImage in,out
INT size=[30],x,y
Put(125) PutE() ;clear the screen
InitGrayImage(in,size,size,dataIn)
InitGrayImage(out,size,size,dataOut)
PrintE("Loading source image...")
LoadPPM5(in,"H6:LENA30G.PPM")
PrintE("Median filter...")
Median3x3(in,out)
Graphics(9)
x=(40-size)/2
y=(48-size)/2
DrawImage(in,x,y)
DrawImage(out,x+40,y)
DO UNTIL CH#$FF OD
CH=$FF
RETURN</syntaxhighlight>
{{out}}
[https://gitlab.com/amarok8bit/action-rosetta-code/-/raw/master/images/Median_filter.png Screenshot from Atari 8-bit computer]
=={{header|Ada}}==
<syntaxhighlight lang="ada">function Median (Picture : Image; Radius : Positive) return Image is
type Extended_Luminance is range 0..10_000_000;
type VRGB is record
Line 66 ⟶ 166:
end loop;
return Result;
end Median;</syntaxhighlight>
The implementation works with an arbitrary window width. The window is specified by its radius ''R''>0. The resulting width is 2''R''+1. The filter uses the original pixels of the image from the median of the window sorted according to the luminance. The image edges are extrapolated using the nearest pixel on the border. Sorting uses binary search. (For practical use, note that median filter is extremely slow.)
The following sample code illustrates use:
<syntaxhighlight lang="ada"> F1, F2 : File_Type;
begin
Open (F1, In_File, "city.ppm");
Line 78 ⟶ 176:
Put_PPM (F2, Median (Get_PPM (F1), 1)); -- Window 3x3
Close (F1);
Close (F2);</syntaxhighlight>
=={{header|BBC BASIC}}==
{{works with|BBC BASIC for Windows}}
This example is a 5 x 5 median filter:
[[Image:greyscale_bbc.jpg|right]]
[[Image:median_bbc.jpg|right]]
<syntaxhighlight lang="bbcbasic"> INSTALL @lib$+"SORTLIB"
Sort% = FN_sortinit(0,0)
Width% = 200
Height% = 200
DIM out&(Width%-1, Height%-1)
VDU 23,22,Width%;Height%;8,16,16,128
*DISPLAY Lenagrey
OFF
REM Do the median filtering:
DIM pix&(24)
C% = 25
FOR Y% = 2 TO Height%-3
FOR X% = 2 TO Width%-3
P% = 0
FOR I% = -2 TO 2
FOR J% = -2 TO 2
pix&(P%) = TINT((X%+I%)*2, (Y%+J%)*2) AND &FF
P% += 1
NEXT
NEXT
CALL Sort%, pix&(0)
out&(X%, Y%) = pix&(12)
NEXT
NEXT Y%
REM Display:
GCOL 1
FOR Y% = 0 TO Height%-1
FOR X% = 0 TO Width%-1
COLOUR 1, out&(X%,Y%), out&(X%,Y%), out&(X%,Y%)
LINE X%*2,Y%*2,X%*2,Y%*2
NEXT
NEXT Y%
REPEAT
WAIT 1
UNTIL FALSE</syntaxhighlight>
=={{header|C}}==
O(n) filter with histogram.
<syntaxhighlight lang="c">#include <stdio.h>
#include <stdlib.h>
#include <fcntl.h>
#include <unistd.h>
#include <ctype.h>
#include <string.h>
typedef struct { unsigned char r, g, b; } rgb_t;
typedef struct {
int w, h;
rgb_t **pix;
} image_t, *image;
typedef struct {
int r[256], g[256], b[256];
int n;
} color_histo_t;
int write_ppm(image im, char *fn)
{
FILE *fp = fopen(fn, "w");
if (!fp) return 0;
fprintf(fp, "P6\n%d %d\n255\n", im->w, im->h);
fwrite(im->pix[0], 1, sizeof(rgb_t) * im->w * im->h, fp);
fclose(fp);
return 1;
}
image img_new(int w, int h)
{
int i;
image im = malloc(sizeof(image_t) + h * sizeof(rgb_t*)
+
im->pix = (rgb_t**)(im + 1);
for (im->pix[0] = (rgb_t*)(im->pix + h), i = 1; i < h; i++)
im->pix[i] = im->pix[i - 1] + w;
return im;
}
int read_num(FILE *f)
{
int n;
while (!fscanf(f, "%d ", &n)) {
if ((n = fgetc(f)) == '#') {
while ((n = fgetc(f)) != '\n')
if (n == EOF) break;
if (n == '\n') continue;
} else return 0;
}
return n;
}
image read_ppm(char *fn)
{
FILE *fp = fopen(fn, "r");
int w, h, maxval;
image im = 0;
if (!fp) return 0;
if (fgetc(fp) != 'P' || fgetc(fp) != '6' || !isspace(fgetc(fp)))
goto bail;
w = read_num(fp);
h = read_num(fp);
maxval = read_num(fp);
if (!w || !h || !maxval) goto bail;
im = img_new(w, h);
fread(im->pix[0], 1, sizeof(rgb_t) * w * h, fp);
bail:
if (fp) fclose(fp);
return im;
}
void del_pixels(image im, int row, int col, int size, color_histo_t *h)
{
int i;
rgb_t *pix;
if (col < 0 || col >= im->w) return;
for (i = row - size; i <= row + size && i < im->h; i++) {
if (i < 0) continue;
pix = im->pix[i] + col;
h->r[pix->r]--;
h->g[pix->g]--;
h->b[pix->b]--;
h->n--;
}
}
void add_pixels(image im, int row, int col, int size, color_histo_t *h)
{
rgb_t *pix;
if (col < 0 || col >= im->w) return;
for (i = row - size; i <= row + size && i < im->h; i++) {
if (i < 0) continue;
pix = im->pix[i] + col;
h->r[pix->r]++;
h->g[pix->g]++;
h->b[pix->b]++;
h->n++;
}
}
void init_histo(image im, int row, int size, color_histo_t*h)
{
int j;
memset(h, 0, sizeof(color_histo_t));
for (j = 0; j < size && j < im->w; j++)
add_pixels(im, row, j, size, h);
}
int median(const int *x, int n)
{
int i;
for (n /= 2, i = 0; i < 256 && (n -= x[i]) > 0; i++);
return i;
}
void median_color(rgb_t *pix, const color_histo_t *h)
{
pix->r = median(h->r, h->n);
pix->g = median(h->g, h->n);
pix->b = median(h->b, h->n);
}
image median_filter(image in, int size)
{
int row, col;
image out = img_new(in->w, in->h);
color_histo_t h;
for (row = 0; row < in->h; row ++) {
for (col = 0; col < in->w; col++) {
if (!col) init_histo(in, row, size, &h);
else {
del_pixels(in, row, col - size, size, &h);
add_pixels(in, row, col + size, size, &h);
}
median_color(out->pix[row] + col, &h);
}
}
return out;
}
int main(int c, char **v)
{
int size;
image in, out;
if (c <= 3) {
printf("Usage: %s size ppm_in ppm_out\n", v[0]);
return 0;
}
size = atoi(v[1]);
printf("filter size %d\n", size);
if (size < 0) size = 1;
in = read_ppm(v[2]);
out = median_filter(in, size);
write_ppm(out, v[3]);
free(in);
free(out);
return 0;
}</syntaxhighlight>
=={{header|D}}==
This uses modules of the [[Bitmap]] and [[Grayscale image]] Tasks.
The implementation uses algorithm described in [http://nomis80.org/ctmf.html Median Filtering in Constant Time]
paper with some slight differences, that shouldn't have impact on complexity.
Currently this code works only on greyscale images.
<syntaxhighlight lang="d">import grayscale_image;
Image!Color medianFilter(uint radius=10, Color)(in Image!Color img)
pure nothrow @safe if (radius > 0) in {
assert(img.nx >= radius && img.ny >= radius);
} body {
alias Hist = uint[256];
static ubyte median(uint no)(in ref Hist cumulative)
pure nothrow @safe @nogc {
size_t localSum = 0;
foreach (immutable k, immutable v; cumulative)
if (v) {
localSum += v;
if (localSum > no / 2)
return k;
}
return 0;
}
// Copy image borders in the result image.
auto result = new Image!Color(img.nx, img.ny);
foreach (immutable y; 0 .. img.ny)
foreach (immutable x; 0 .. img.nx)
if (x < radius || x > img.nx - radius - 1 ||
y < radius || y > img.ny - radius - 1)
result[x, y] = img[x, y];
enum edge = 2 * radius + 1;
auto hCol = new Hist[img.nx];
// Create histogram columns.
foreach (immutable y; 0 .. edge - 1)
foreach (immutable x, ref hx; hCol)
hx[img[x, y]]++;
foreach (immutable y; radius .. img.ny - radius) {
// Add to each histogram column lower pixel.
foreach (immutable x, ref hx; hCol)
hx[img[x, y + radius]]++;
// Calculate main Histogram using first edge-1 columns.
Hist H;
foreach (immutable x; 0 .. edge - 1)
foreach (immutable k, immutable v; hCol[x])
if (v)
H[k] += v;
foreach (immutable x; radius .. img.nx - radius) {
// Add right-most column.
foreach (immutable k, immutable v; hCol[x + radius])
if (v)
H[k] += v;
result[x, y] = Color(median!(edge ^^ 2)(H));
// Drop left-most column.
foreach (immutable k, immutable v; hCol[x - radius])
if (v)
H[k] -= v;
}
// Substract the upper pixels.
foreach (immutable x, ref hx; hCol)
hx[img[x, y - radius]]--;
}
return result;
}
version (median_filter_main)
void main() { // Demo.
loadPGM!Gray(null, "lena.pgm").
medianFilter!10
.savePGM("lena_median_r10.pgm");
}</syntaxhighlight>
Compile with -version=median_filter_main to run the demo.
=={{header|Delphi}}==
{{works with|Delphi|6.0}}
{{libheader|SysUtils,StdCtrls}}
[[File:DelphiMedianFilter.png|frame|none]]
<syntaxhighlight lang="Delphi">
{-------------------------------------------------------------------------------}
type THistogram = record
Bins: array [0..255] of integer;
Colors: array [0..255] of TRGBTriple;
end;
procedure MedianFilter(Src,Dest: TBitmap; WindowX, WindowY: integer);
var x, y, X1, Y1, med, md, dl, delta_l, WX2, WY2: integer;
var I, MedSum, XStart,XEnd, YStart,YEnd, MedInx: integer;
var middle: integer;
var Histogram: THistogram;
var u: byte;
var Color: TRGBTriple;
var SrcRows,DestRows: TRGBTripleRowArray;
begin
WindowX:=WindowX * 2 -1;
WindowY:=WindowY * 2 -1;
Src.PixelFormat:=pf24Bit;
Dest.PixelFormat:=pf24Bit;
Dest.Width:=Src.Width;
Dest.Height:=Src.Height;
SetLength(SrcRows,Src.Height);
SetLength(DestRows,Dest.Height);
{Capture scan lines of both source and destiantion bitmaps}
for Y:=0 to Src.Height-1 do SrcRows[Y]:=Src.ScanLine[Y];
for Y:=0 to Dest.Height-1 do DestRows[Y]:=Dest.ScanLine[Y];
WX2 := WindowX div 2;
WY2 := WindowY div 2;
middle := (WindowX * WindowY-1) div 2;
for y := 0 to SRC.Height-1 do
begin
{ Determine the histogram and median for the first element of each row}
YStart:=Y - WY2;
YEnd:=Y + WY2;
{ histogram reset }
for I := 0 to 255 do Histogram.Bins[I] := 0;
{recalculation of the histogram for the start element row=y, col=0 }
for Y1 := YStart to YEnd do
for X1 := -WX2 to WX2 do
begin
{It is the first pixel on the row, so don't worry about right edge}
if (Y1>=0) and (Y1<SRC.Height) and (X1>=0) then Color:=SrcRows[Y1][X1] else Color:=MakeRBGTriple(0,0,0); // Color:=SrcRows[y][0];
U:=RGBToGray(Color);
inc(Histogram.Bins[U]);
Histogram.Colors[U]:=Color;
end;
{ now determine the median }
MedSum := 0;
for MedInx := 0 to 255 do
begin
inc(MedSum,Histogram.Bins[MedInx]);
if MedSum > middle then break;
end;
med := MedInx;
delta_l := MedSum - Histogram.Bins[MedInx];
DestRows[Y][0]:=Histogram.Colors[MedInx];
{ Loop through each column in this row}
for x := 1 to Src.Width-1 do
begin
XStart := x-wx2-1;
XEnd := x+wx2;
{ go to next column }
for Y1 := YStart to YEnd do
begin
if (XStart >= 0) and (Y1 >= 0) and (Y1 < SRC.Height) then Color:=SrcRows[Y1][XStart] else Color:=MakeRBGTriple(0,0,0); // Color:=SrcRows[Y][X];
U:=RGBToGray(Color);
if Histogram.Bins[u]>0 then dec(Histogram.Bins[u]);
if u < med then dec(delta_l);
if (XEnd < Src.Width) and (Y1 >= 0) and (Y1 < SRC.Height) then Color:=SrcRows[Y1][XEnd] else Color:=MakeRBGTriple(0,0,0); // Color:=SrcRows[Y][X];
U:=RGBToGray(Color);
inc(Histogram.Bins[u]);
Histogram.Colors[U]:=Color;
if u < med then inc(delta_l);
end;
{ update new median }
dl := delta_l;
md := med;
if dl > middle then
begin
while dl > middle do
begin
dec(md);
if Histogram.Bins[md] > 0 then
dec(dl,Histogram.Bins[md]);
end;
end
else
begin
while dl + Histogram.Bins[md] <= middle do
begin
if Histogram.Bins[md] > 0 then inc(dl,Histogram.Bins[md]);
inc(md);
end;
end;
delta_l := dl;
med := md;
DestRows[Y][X]:= Histogram.Colors[med];
end; { x loop}
end; { y loop}
end;
</syntaxhighlight>
{{out}}
<pre>
Elapsed Time: 110.287 ms.
</pre>
=={{header|GDL}}==
GDL has no inbuilt median filter function, which is native in IDL. This example is based on pseudocode here: http://en.wikipedia.org/wiki/Median_filter#2D_median_filter_pseudo_code, however, it works with 1D arrays only. It does not process boundaries.
<syntaxhighlight lang="gdl">
FUNCTION MEDIANF,ARRAY,WINDOW
RET=fltarr(N_ELEMENTS(ARRAY),1)
EDGEX=WINDOW/2
FOR X=EDGEX, N_ELEMENTS(ARRAY)-EDGEX DO BEGIN
PRINT, "X", X
COLARRAY=fltarr(WINDOW,1)
FOR FX=0, WINDOW-1 DO BEGIN
COLARRAY[FX]=ARRAY[X + FX - EDGEX]
END
T=COLARRAY[SORT(COLARRAY)]
RET[X]=T[WINDOW/2]
END
RETURN, RET
END
</syntaxhighlight>
Usage:
<syntaxhighlight lang="gdl">Result = MEDIANF(ARRAY, WINDOW)</syntaxhighlight>
=={{header|Go}}==
Implemented with existing GetPx/SetPx functions at Grayscale image task. It could be sped up by putting code in the raster package, but if you're concerned about speed, you should implement one of the O(n) algorithms available.
<syntaxhighlight lang="go">package main
// Files required to build supporting package raster are found in:
// * Bitmap
// * Grayscale image
// * Read a PPM file
// * Write a PPM file
import (
"fmt"
"raster"
)
var g0, g1 *raster.Grmap
var ko [][]int
var kc []uint16
var mid int
func init() {
// hard code box of 9 pixels
ko = [][]int{
{-1, -1}, {0, -1}, {1, -1},
{-1, 0}, {0, 0}, {1, 0},
{-1, 1}, {0, 1}, {1, 1}}
kc = make([]uint16, len(ko))
mid = len(ko) / 2
}
func main() {
// Example file used here is Lenna50.jpg from the task "Percentage
// difference between images" converted with with the command
// convert Lenna50.jpg -colorspace gray Lenna50.ppm
// It shows very obvious compression artifacts when viewed at higher
// zoom factors.
b, err := raster.ReadPpmFile("Lenna50.ppm")
if err != nil {
fmt.Println(err)
return
}
g0 = b.Grmap()
w, h := g0.Extent()
g1 = raster.NewGrmap(w, h)
for y := 0; y < h; y++ {
for x := 0; x < w; x++ {
g1.SetPx(x, y, median(x, y))
}
}
// side by side comparison with input file shows compression artifacts
// greatly smoothed over, although at some loss of contrast.
err = g1.Bitmap().WritePpmFile("median.ppm")
if err != nil {
fmt.Println(err)
}
}
func median(x, y int) uint16 {
var n int
// construct sorted list as pixels are read. insertion sort can't be
// beat for a small number of items, plus there would be lots of overhead
// just to get numbers in and out of a library sort routine.
for _, o := range ko {
// read a pixel of the kernel
c, ok := g0.GetPx(x+o[0], y+o[1])
if !ok {
continue
}
// insert it in sorted order
var i int
for ; i < n; i++ {
if c < kc[i] {
for j := n; j > i; j-- {
kc[j] = kc[j-1]
}
break
}
}
kc[i] = c
n++
}
// compute median from sorted list
switch {
case n == len(kc): // the usual case, pixel with complete neighborhood
return kc[mid]
case n%2 == 1: // edge case, odd number of pixels
return kc[n/2]
}
// else edge case, even number of pixels
m := n / 2
return (kc[m-1] + kc[m]) / 2
}</syntaxhighlight>
=={{header|J}}==
The task could be solved the following way. First, for each pixel of input, collect pixels which fall into the corresponding window, where median value will be calculated. Then, for each window - the set of pixels - find the median value. To compare 3-channel pixels we first convert them into 1-channel gray values.
The following verbs are used to work with bitmaps:
<syntaxhighlight lang="j">
makeRGB=: 0&$: : (($,)~ ,&3)
toGray=: <. @: (+/) @: (0.2126 0.7152 0.0722 & *)"1
</syntaxhighlight>
We'll determine the window as a square zone around each pixel, with the given pixel in the center of the zone. Such a window always have odd height and width. We'll say the window radius is 0 if the window contain only the given pixel - in this case the resulting picture will be identical to the input. The radius is 1 if the window is 3x3 pixels, with given pixel in the center. Radius is 2 if the window is 5x5 pixels, with given pixel in the center, etc.
To get all pixels in the window, first calculate coordinates - or indexes - of those pixels. For the pixels on the edges of the input bitmap, include only those indexes which correspond to actually existing pixels - no negative indexes and no indexes outside of the bitmap boundaries.
<syntaxhighlight lang="j">
median_filter =: dyad define
win =. y -~ i. >: +: y
height =. {: }: $ x
width =. {. }: $ x
h_indexes =. < @ (#~ >:&0 * <&height) @ (win&+)"0 i. height
w_indexes =. < @ (#~ >:&0 * <&width) @ (win&+)"0 i. width
sets =. w_indexes < @ ({&x) @ < @ ,"0 0/ h_indexes
medians =. ({~ <. @ -: @ {. @ $) @ ({~ /: @: toGray) @ (,/) @ > sets
)
</syntaxhighlight>
Example:
<syntaxhighlight lang="j">
] bmp =. ?. 256 + makeRGB 4 5
34 39 168
133 133 40
210 137 244
66 183 114
211 241 75
212 68 13
91 246 128
203 236 213
162 92 165
90 203 161
104 124 113
199 61 60
135 179 241
142 156 125
64 77 61
130 70 200
114 32 55
94 211 182
29 49 252
116 139 217
bmp median_filter 1
133 133 40
210 137 244
210 137 244
90 203 161
90 203 161
104 124 113
133 133 40
66 183 114
210 137 244
66 183 114
212 68 13
104 124 113
142 156 125
142 156 125
116 139 217
130 70 200
104 124 113
142 156 125
142 156 125
116 139 217
</syntaxhighlight>
=={{header|Java}}==
The class in the [[Bitmap]] task is reused for this task with an additional method to filter the image using the Wikipedia pseudo-code.
The program is tested with the left half of the sample image file, Medianfilterp.png, in the Wikipedia article.
<syntaxhighlight lang="java">
import java.awt.Color;
import java.awt.Graphics;
import java.awt.Image;
import java.awt.image.BufferedImage;
import java.awt.image.RenderedImage;
import java.io.File;
import java.io.IOException;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import javax.imageio.ImageIO;
public final class MedianFilter {
public static void main(String[] aArgs) {
try {
BufferedImage image = ImageIO.read( new File("beforeFilter.png") );
BasicBitmapStorage bitmap = new BasicBitmapStorage(image.getWidth(null), image.getHeight(null));
for ( int y = 0; y < image.getHeight(null); y++ ) {
for ( int x = 0; x < image.getWidth(null); x++ ) {
bitmap.setPixel(x, y, new Color(image.getRGB(x, y), true));
}
}
bitmap.medianFilter(3, 3);
File fileAfterFilter = new File("afterFilter.png");
ImageIO.write((RenderedImage) bitmap.getImage(), "png", fileAfterFilter);
} catch (IOException ioe) {
ioe.printStackTrace();
}
}
}
final class BasicBitmapStorage {
public BasicBitmapStorage(int aWidth, int aHeight) {
image = new BufferedImage(aWidth, aHeight, BufferedImage.TYPE_INT_RGB);
}
public void fill(Color aColor) {
Graphics graphics = image.getGraphics();
graphics.setColor(aColor);
graphics.fillRect(0, 0, image.getWidth(), image.getHeight());
}
public Color getPixel(int aX, int aY) {
return new Color(image.getRGB(aX, aY));
}
public void setPixel(int aX, int aY, Color aColor) {
image.setRGB(aX, aY, aColor.getRGB());
}
public Image getImage() {
return image;
}
public void medianFilter(int aWindowWidth, int aWindowHeight) {
List<Color> window = Stream.generate( () -> Color.BLACK )
.limit(aWindowWidth * aWindowHeight).collect(Collectors.toList());
final int edgeX = aWindowWidth / 2;
final int edgeY = aWindowHeight / 2;
Comparator<Color> luminanceComparator = (one, two) -> Double.compare(luminance(one), luminance(two));
for ( int x = edgeX; x < image.getWidth() - edgeX; x++ ) {
for ( int y = edgeY; y < image.getHeight() - edgeY; y++ ) {
int i = 0;
for ( int fx = 0; fx < aWindowWidth; fx++ ) {
for ( int fy = 0; fy < aWindowHeight; fy++ ) {
window.set(i, getPixel(x + fx - edgeX, y + fy - edgeY));
i += 1;
}
}
Collections.sort(window, luminanceComparator);
setPixel(x, y, window.get(aWindowWidth * aWindowHeight / 2));
}
}
}
private double luminance(Color aColor) {
return 0.2126 * aColor.getRed() + 0.7152 * aColor.getGreen() + 0.0722 * aColor.getBlue();
}
private final BufferedImage image;
}
</syntaxhighlight>
{{ out }}
[[Media:beforeFilter.png]] & [[Media:afterFilter.png]]
=={{header|Julia}}==
{{works with|Julia|0.6}}
<syntaxhighlight lang="julia">using Images, ImageFiltering, FileIO
Base.isless(a::RGB{T}, b::RGB{T}) where T =
red(a) < red(b) || green(a) < green(b) || blue(a) < blue(b)
Base.middle(x::RGB) = x
img = load("data/lenna100.jpg")
mapwindow(median!, img, (3, 3))</syntaxhighlight>
=={{header|Kotlin}}==
We reuse the class in the [[Bitmap]] task for this and add a member function to filter the image as per the Wikipedia pseudo-code. The colors in the Window array are sorted by their luminance.
To test the function we use the left half of the sample image file (Medianfilterp.png) in the Wikipedia article and see if we can get close to the right half.
<syntaxhighlight lang="scala">// Version 1.2.41
import java.awt.Color
import java.awt.Graphics
import java.awt.image.BufferedImage
import java.io.File
import javax.imageio.ImageIO
class BasicBitmapStorage(width: Int, height: Int) {
val image = BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR)
fun fill(c: Color) {
val g = image.graphics
g.color = c
g.fillRect(0, 0, image.width, image.height)
}
fun setPixel(x: Int, y: Int, c: Color) = image.setRGB(x, y, c.getRGB())
fun getPixel(x: Int, y: Int) = Color(image.getRGB(x, y))
fun medianFilter(windowWidth: Int, windowHeight: Int) {
val window = Array(windowWidth * windowHeight) { Color.black }
val edgeX = windowWidth / 2
val edgeY = windowHeight / 2
val compareByLuminance = {
c: Color -> 0.2126 * c.red + 0.7152 * c.green + 0.0722 * c.blue
}
for (x in edgeX until image.width - edgeX) {
for (y in edgeY until image.height - edgeY) {
var i = 0
for (fx in 0 until windowWidth) {
for (fy in 0 until windowHeight) {
window[i] = getPixel(x + fx - edgeX, y + fy - edgeY)
i++
}
}
window.sortBy(compareByLuminance)
setPixel(x, y, window[windowWidth * windowHeight / 2])
}
}
}
}
fun main(args: Array<String>) {
val img = ImageIO.read(File("Medianfilterp.png"))
val bbs = BasicBitmapStorage(img.width / 2, img.height)
with (bbs) {
for (y in 0 until img.height) {
for (x in 0 until img.width / 2) {
setPixel(x, y, Color(img.getRGB(x, y)))
}
}
medianFilter(3, 3)
val mfFile = File("Medianfilterp2.png")
ImageIO.write(image, "png", mfFile)
}
}</syntaxhighlight>
{{output}}
<pre>
Similar to right-half of Wikipedia image - color definition and brightness seem better but remaining distortion more evident.
</pre>
=={{header|Mathematica}}/{{header|Wolfram Language}}==
<syntaxhighlight lang="mathematica">MedianFilter[img,n]</syntaxhighlight>
=={{header|Nim}}==
{{trans|Kotlin}}
{{libheader|imageman}}
{{libheader|stb_image-Nim}}
<br>
Compile with command <code>nim c -d:imagemanlibpng=false -d:imagemanlibjpeg=false median_filter.nim</code> to
constrain "imageman" to use the library "stb_image" to open the PNG file. It seems that "imageman" internal
procedure has some difficulties to open PNG files using a palette.
<syntaxhighlight lang="nim">import algorithm
import imageman
func luminance(color: ColorRGBF64): float =
0.2126 * color.r + 0.7152 * color.g + 0.0722 * color.b
proc applyMedianFilter(img: var Image; windowWidth, windowHeight: Positive) =
var window = newSeq[ColorRGBF64](windowWidth * windowHeight)
let edgeX = windowWidth div 2
let edgeY = windowHeight div 2
for x in edgeX..<(img.width - edgeX):
for y in edgeY..<(img.height - edgeY):
var i = 0
for fx in 0..<windowWidth:
for fy in 0..<windowHeight:
window[i] = img[x + fx - edgeX, y + fy - edgeY]
inc i
window = window.sortedByIt(luminance(it))
img[x, y] = window[windowWidth * windowHeight div 2]
when isMainModule:
let fullImage = loadImage[ColorRGBF64]("Medianfilterp.png")
# Extract left part of the image.
var image = fullImage[0..<(fullImage.width div 2), 0..<fullImage.height]
image.applyMedianFilter(3, 3)
savePNG(image, "Medianfilterp_3x3.png")</syntaxhighlight>
=={{header|OCaml}}==
<syntaxhighlight lang="ocaml">let color_add (r1,g1,b1) (r2,g2,b2) =
( (r1 + r2),
(g1 + g2),
Line 252 ⟶ 1,097:
done;
done;
(res)</
an alternate version of the function <
<syntaxhighlight lang="ocaml">let median_value img radius =
let samples = (radius*2+1) * (radius*2+1) in
let sample = Array.make samples (0,0,0) in
Line 274 ⟶ 1,119:
then sample.(mid+1)
else (color_div (color_add sample.(mid)
sample.(mid+1)) 2)</
=={{header|Perl}}==
<syntaxhighlight lang="perl">use strict 'vars';
use warnings;
use PDL;
use PDL::Image2D;
my $image = rpic 'plasma.png';
my $smoothed = med2d $image, ones(3,3), {Boundary => Truncate};
wpic $smoothed, 'plasma_median.png';</syntaxhighlight>
Compare offsite images: [https://github.com/SqrtNegInf/Rosettacode-Perl5-Smoke/blob/master/ref/plasma.png plasma.png] vs.
[https://github.com/SqrtNegInf/Rosettacode-Perl5-Smoke/blob/master/ref/plasma_median.png plasma_median.png]
=={{header|Phix}}==
{{trans|Go}}
Requires read_ppm() from [[Bitmap/Read_a_PPM_file#Phix|Read_a_PPM_file]], write_ppm() from [[Bitmap/Write_a_PPM_file#Phix|Write_a_PPM_file]],
which are both now part of demo\rosetta\ppm.e. Results may be verified with demo\rosetta\viewppm.exw
<syntaxhighlight lang="phix">-- demo\rosetta\Bitmap_Median_filter.exw
include ppm.e
constant neigh = {{-1,-1},{0,-1},{1,-1},
{-1, 0},{0, 0},{1, 0},
{-1, 1},{0, 1},{1, 1}}
--constant neigh = {{-2,-2},{-1,-2},{0,-2},{1,-2},{2,-2},
-- {-2,-1},{-1,-1},{0,-1},{1,-1},{2,-1},
-- {-2, 0},{-1, 0},{0, 0},{1, 0},{2, 0},
-- {-2, 1},{-1, 1},{0, 1},{1, 1},{2, 1},
-- {-2, 2},{-1, 2},{0, 2},{1, 2},{2, 2}}
sequence kn = repeat(0,length(neigh))
function median(sequence image)
integer h = length(image),
w = length(image[1])
for i=1 to length(image) do
for j=1 to length(image[i]) do
integer n = 0, c, p, x, y
for k=1 to length(neigh) do
x = i+neigh[k][1]
y = j+neigh[k][2]
if x>=1 and x<=h
and y>=1 and y<=w then
n += 1
c = image[x,j]
p = n
while p>1 do
if c>kn[p-1] then exit end if
kn[p] = kn[p-1]
p -= 1
end while
kn[p] = c
end if
end for
if and_bits(n,1) then
c = kn[(n+1)/2]
else
c = floor((kn[n/2]+kn[n/2+1])/2)
end if
image[i,j] = c
end for
end for
return image
end function
sequence img = read_ppm("Lena.ppm")
img = median(img)
write_ppm("LenaMedian.ppm",img)</syntaxhighlight>
=={{header|PicoLisp}}==
<syntaxhighlight lang="picolisp">(de ppmMedianFilter (Radius Ppm)
(let Len (inc (* 2 Radius))
(make
(chain (head Radius Ppm))
(for (Y Ppm T (cdr Y))
(NIL (nth Y Len)
(chain (tail Radius Y)) )
(link
(make
(chain (head Radius (get Y (inc Radius))))
(for (X (head Len Y) T)
(NIL (nth X 1 Len)
(chain (tail Radius (get X (inc Radius)))) )
(link
(cdr
(get
(sort
(mapcan
'((Y)
(mapcar
'((C)
(cons
(+
(* (car C) 2126) # Red
(* (cadr C) 7152) # Green
(* (caddr C) 722) ) # Blue
C ) )
(head Len Y) ) )
X ) )
(inc Radius) ) ) )
(map pop X) ) ) ) ) ) ) )</syntaxhighlight>
Test using 'ppmRead' from [[Bitmap/Read a PPM file#PicoLisp]] and 'ppmWrite'
from [[Bitmap/Write a PPM file#PicoLisp]]:
<pre>(ppmWrite (ppmMedianFilter 2 (ppmRead "Lenna100.ppm")) "a.ppm")</pre>
=={{header|Python}}==
{{works with|Python|2.6}}
{{libheader|PIL}}
<syntaxhighlight lang="python">import Image, ImageFilter
im = Image.open('image.ppm')
median = im.filter(ImageFilter.MedianFilter(3))
median.save('image2.ppm')</syntaxhighlight>
=={{header|Racket}}==
Due to the use of flomaps the solution below works for all types of images.
<syntaxhighlight lang="racket">
#lang racket
(require images/flomap math)
(define lena <<paste image of Lena here>> )
(define bm (send lena get-bitmap))
(define fm (bitmap->flomap bm))
(flomap->bitmap
(build-flomap
4 (send bm get-width) (send bm get-height)
(λ (k x y)
(define (f x y) (flomap-ref fm k x y))
(median < (list (f (- x 1) (- y 1))
(f (- x 1) y)
(f (- x 1) (+ y 1))
(f x (- y 1))
(f x y)
(f x (+ y 1))
(f (+ x 1) (- y 1))
(f (+ x 1) y)
(f (+ x 1) (+ y 1)))))))
</syntaxhighlight>
=={{header|Raku}}==
(formerly Perl 6)
Clone of Perl 5, for now.
<syntaxhighlight lang="raku" line>use PDL:from<Perl5>;
use PDL::Image2D:from<Perl5>;
my $image = rpic 'plasma.png';
my $smoothed = med2d($image, ones(3,3), {Boundary => 'Truncate'});
wpic $smoothed, 'plasma_median.png';</syntaxhighlight>
Compare offsite images: [https://github.com/SqrtNegInf/Rosettacode-Perl6-Smoke/blob/master/ref/plasma-perl6.png plasma.png] vs.
[https://github.com/SqrtNegInf/Rosettacode-Perl6-Smoke/blob/master/ref/plasma_median.png plasma_median.png]
=={{header|Ruby}}==
{{trans|Tcl}}
<syntaxhighlight lang="ruby">class Pixmap
def median_filter(radius=3)
radius += 1 if radius.even?
filtered = self.class.new(@width, @height)
pb = ProgressBar.new(@height) if $DEBUG
@height.times do |y|
@width.times do |x|
window = []
(x - radius).upto(x + radius).each do |win_x|
(y - radius).upto(y + radius).each do |win_y|
win_x = 0 if win_x < 0
win_y = 0 if win_y < 0
win_x = @width-1 if win_x >= @width
win_y = @height-1 if win_y >= @height
window << self[win_x, win_y]
end
end
# median
filtered[x, y] = window.sort[window.length / 2]
end
pb.update(y) if $DEBUG
end
pb.close if $DEBUG
filtered
end
end
class RGBColour
# refactoring
def luminosity
Integer(0.2126*@red + 0.7152*@green + 0.0722*@blue)
end
def to_grayscale
l = luminosity
self.class.new(l, l, l)
end
# defines how to compare (and hence, sort)
def <=>(other)
self.luminosity <=> other.luminosity
end
end
class ProgressBar
def initialize(max)
$stdout.sync = true
@progress_max = max
@progress_pos = 0
@progress_view = 68
$stdout.print "[#{'-'*@progress_view}]\r["
end
def update(n)
new_pos = n * @progress_view/@progress_max
if new_pos > @progress_pos
@progress_pos = new_pos
$stdout.print '='
end
end
def close
$stdout.puts '=]'
end
end
bitmap = Pixmap.open('file')
filtered = bitmap.median_filter</syntaxhighlight>
=={{header|Tcl}}==
{{works with|Tcl|8.5}}
{{libheader|Tk}}
<syntaxhighlight lang="tcl">package require Tk
# Set the color of a pixel
proc applyMedian {srcImage x y -> dstImage} {
set x0 [expr {$x==0 ? 0 : $x-1}]
set y0 [expr {$y==0 ? 0 : $y-1}]
set x1 $x
set y1 $y
set x2 [expr {$x+1==[image width $srcImage] ? $x : $x+1}]
set y2 [expr {$y+1==[image height $srcImage] ? $y : $y+1}]
set r [set g [set b {}]]
foreach X [list $x0 $x1 $x2] {
foreach Y [list $y0 $y1 $y2] {
lassign [$srcImage get $X $Y] rPix gPix bPix
lappend r $rPix
lappend g $gPix
lappend b $bPix
}
}
set r [lindex [lsort -integer $r] 4]
set g [lindex [lsort -integer $g] 4]
set b [lindex [lsort -integer $b] 4]
$dstImage put [format "#%02x%02x%02x" $r $g $b] -to $x $y
}
# Apply the filter to the whole image
proc medianFilter {srcImage {dstImage ""}} {
if {$dstImage eq ""} {
set dstImage [image create photo]
}
set w [image width $srcImage]
set h [image height $srcImage]
for {set x 0} {$x < $w} {incr x} {
for {set y 0} {$y < $h} {incr y} {
applyMedian $srcImage $x $y -> $dstImage
}
}
return $dstImage
}
# Demonstration code using the Tk widget demo's teapot image
image create photo teapot -file $tk_library/demos/images/teapot.ppm
pack [labelframe .src -text Source] -side left
pack [label .src.l -image teapot]
update
pack [labelframe .dst -text Median] -side left
pack [label .dst.l -image [medianFilter teapot]]</syntaxhighlight>
=={{header|Wren}}==
{{libheader|DOME}}
This follows the Wikipedia pseudo-code for the median filter, sorting the colors by their luminance, and displays the 'before' and 'after' images side by side on the canvas. Results are as expected though remaining corruption seems more prominent than on Wikipedia image.
<syntaxhighlight lang="wren">import "graphics" for Canvas, ImageData, Color
import "dome" for Window
class MedianFilter {
construct new(filename, filename2, windowWidth, windowHeight) {
Window.title = "Median filter"
var image = ImageData.loadFromFile(filename)
Window.resize(image.width, image.height)
Canvas.resize(image.width, image.height)
_ww = windowWidth
_wh = windowHeight
// split off the left half
_image = ImageData.create(filename2, image.width/2, image.height)
_name = filename2
for (x in 0...image.width/2) {
for (y in 0...image.height) _image.pset(x, y, image.pget(x, y))
}
// display it on the left before filtering
_image.draw(0, 0)
}
luminance(c) { 0.2126 * c.r + 0.7152 * c.g + 0.0722 * c.b }
medianFilter(windowWidth, windowHeight) {
var window = List.filled(windowWidth * windowHeight, Color.black)
var edgeX = (windowWidth / 2).floor
var edgeY = (windowHeight / 2).floor
var comparer = Fn.new { |a, b| luminance(a) < luminance(b) }
for (x in edgeX..._image.width - edgeX) {
for (y in edgeY..._image.height - edgeY) {
var i = 0
for (fx in 0...windowWidth) {
for (fy in 0...windowHeight) {
window[i] = _image.pget(x + fx - edgeX, y + fy - edgeY)
i = i + 1
}
}
window.sort(comparer)
_image.pset(x, y, window[((windowWidth * windowHeight)/2).floor])
}
}
}
init() {
medianFilter(_ww, _wh)
// display it on the right after filtering
_image.draw(_image.width, 0)
// save it to a file
_image.saveToFile(_name)
}
update() {}
draw(alpha) {}
}
var Game = MedianFilter.new("Medianfilterp.png", "Medianfilterp2.png", 3, 3)</syntaxhighlight>
=={{header|zkl}}==
Uses Image Magick and the PPM class from http://rosettacode.org/wiki/Bitmap/Bresenham%27s_line_algorithm#zkl
<syntaxhighlight lang="zkl">fcn medianFilter(img){ //-->new image
var [const] window=[-2..2].walk(), edge=(window.len()/2); // 5x5 window
MX,MY,new := img.w,img.h,PPM(MX,MY);
pixel,pixels:=List(),List();
foreach x,y in ([edge..MX-edge-1],[edge..MY-edge-1]){
pixels.clear();
foreach ox,oy in (window,window){ // construct sorted list as pixels are read.
pixels.merge(pixel.clear(img[x+ox, y+oy])); // merge sort two lists
}
new[x,y]=pixels[4]; // median value
}
new
}</syntaxhighlight>
<syntaxhighlight lang="zkl">filtered:=medianFilter(PPM.readJPGFile("lena.jpg"));
filtered.writeJPGFile("lenaMedianFiltered.zkl.jpg");</syntaxhighlight>
See the [http://www.zenkinetic.com/Images/RosettaCode/lenaMedianFiltered.zkl.jpg filtered image]
and the [http://www.zenkinetic.com/Images/RosettaCode/lena.jpg orginal].
{{omit from|PARI/GP}}
| |||