Filter function
|
|
function name |
describle |
|
1 |
Rotate |
Rotates image in any size |
|
2 |
reverse |
reverse the image |
|
3 |
Resize |
Resizes image in any size |
|
4 |
paint |
redistribute each color channel of an image |
|
5 |
Mosaic |
mosaic the image |
|
6 |
mirror |
get a mirror image |
|
7 |
Lap_sharp |
sharp the image |
|
8 |
imThreshold |
Creates a "binary" image with values distributed according to the threshold parameter |
|
9 |
imconvert |
overturn an image in a certain diretion |
|
10 |
Gauss_sharp |
harp the image |
|
11 |
exposal |
get an exposal image |
|
12 |
emboss |
create emboss of an image |
|
13 |
contrast |
adjust contrast of an image |
|
14 |
color_balance |
increases or decreases the brightness of RGB color channels in the image independently |
|
15 |
col2gray |
convert an image to a grayscale image |
|
16 |
bright |
adjust brightness of an image |
|
17 |
Blur |
blur the image |
1. Rotate - Rotates image in any size
Calling Sequence
img = Rotate(im,angle);
Parameters
im: Input matrice.
angle: the angle that you want to rotate by
-360 degree <= angle <= 360 degree
Description
Rotate an image in angle
Examples
im = imread("lena.png");
img=Rotate(im,30);
2. reverse - reverse the
image
Calling Sequence:
img = reverse(im)
Parmeters:
im: matrix of an input image
img: output image matrix
Description:
we can get this effect using formula as follow:
img=im*(-1)+255
Example:
im = imread("lena.png");
img = reverse(im);
3. Resize - Resizes image in any size
Calling Sequence
img = Resize(im,Height,Width);
Parameters
im: Input matrice.
Height:rows of the ouput matrice
Width:coloums of the ouput matrice
Description
resize an image in any size
Examples
im = imread("lena.png");
img=Resize(im,4);
4. paint - redistribute each
color channel of an image
Calling Sequence:
img = paint(im,red,green,blue)
Parmeters:
im: matrix of an input image
red: set contribution to R channel
green: set contribution to G channel
blue: set contribution to B channel
img: output image matrix
Description:
This function redistributes the rate of the three color channel in an image.First,we get a variable "gray" as we do in function "col2gray".Then recompute each color channel like this: new_red=(red.*gray)/255;
Example:
im = imread("lena.png");
img = paint(im,255,0,0);
5. Mosaic- mosaic the image
Calling Sequence:
img = Mosaic(im,n)
Parmeters:
im: matrix of an input image
n: mosaic paremeter ,the larger ,the blurrier (5<=n<=20)
img: output image matrix
Description:
mosaic the image
Example:
im = imread("lena.png");
img = Mosaic(im,8);
6. mirror - get a mirror
image
Calling Sequence:
img = mirror(im,my_select)
Parmeters:
im: matrix of an input image
my_select: select a manner for mirror
img: output image matrix
Description:
This function get a horizontal or vertical mirror image.
Example:
im = imread("lena.png");
img = mirror(im,1);
7. Lap_sharp- sharp the
image
Calling Sequence:
img = Lap_sharp(im)
Parmeters:
im: matrix of an input image
img: output image matrix
Description:
Lap_sharp The function Lap_sharp calculates the convolution of the input image "im"
with the Laplacian kernel of a specified size apertureSize and stores the result in "img".
Example:
im = imread("lena.png");
img = Lap_sharp(im);
8. imThreshold
- Creates a "binary" image with values distributed according to the
threshold parameter
Calling Sequence:
img = imThreshold(im,rate)
Parmeters:
im: matrix of an input image
rate: a value between 0 and 100,it shows the degree of threshold
img: output image matrix
Description:
pixels with values below the threshold ("dark") are assigned one value (e.g., black) while those
above the threshold ("light") are set to antoher value (e.g., white)
Example:
im = imread("lena.png");
img = imThreshold(im,25);
9. imconvert
- overturn an image in a certain diretion
Calling Sequence:
img = imconvert(im,my_select)
Parmeters:
im: matrix of an input image
my_select: select a manner for converting
img: output image matrix
Description:
This function provides three manner for fast overturn.
1) horizontal 180
2) deasil 90
3) anticlockwise 90
Example:
im = imread("lena.png");
img = imconvert(im,2);
10. Gauss_sharp- harp the
image
Calling Sequence:
img = Gauss_sharp(im)
Parmeters:
im: matrix of an input image
img: output image matrix
Description:
Gauss_sharp The function Gauss_sharp calculates the convolution of the input image "im"
with the Gauss kernel of a specified size apertureSize and stores the result in "img".
Example:
im = imread("lena.png");
img = Gauss_sharp(im);
11. exposal - get an exposal
image
Calling Sequence:
img = exposal(im)
Parmeters:
im: matrix of an input image
img: output image matrix
Description:
if a color value of a pixel < 128,then set this value be (255-thisValue),else no change.
Then we can get an effect as we see a negative in a studio
Example:
im = imread("lena.png");
img = exposal(im);
12. emboss - create emboss of
an image
Calling Sequence:
img = emboss(im,n)
Parmeters:
im: matrix of an input image
n: select a manner for embossing
img: output image matrix
Description:
We provide eight methods for getting an embossed image,that is,southwest south southeast west east northwest north northeast.
Example:
im = imread("lena.png");
img = emboss(im,2);
13. contrast -
adjust contrast of an image
Calling Sequence:
img = contrast(im,rate)
Parmeters:
im: matrix of an input image
rate: a value between -100 and 100,it shows the degree of contrast
img: output image matrix
Description:
This function adjust contrast of an input image.It relates to the diffence between bright and dark.
The diffence is clearer if "rate" is larger.
Example:
im = imread("lena.png");
img = contrast(im,25);
14. color_balance - increases or
decreases the brightness of RGB color channels in the image independently
Calling Sequence:
img = color_balance(im,red,green,blue)
Parmeters:
im: matrix of an input image
red: set contribution to R channel
green: set contribution to G channel
blue: set contribution to B channel
img: output image matrix
Description:
some colors can be highlighted, while other are suppressed or remain untouched.Color balance may be quite handful, e.g., when viewing an image on a display with different color calibration than the calibration of the device the image was acquired with. Another field of usage is art photography and video processing, as different colors possess the ability to evoke specific emotions.
Example:
im = imread("lena.png");
img = color_balance(im,255,0,0);
15. col2gray - convert an image to a grayscale image
Calling Sequence:
img = col2gray(im,my_select)
Parmeters:
im: matrix of an input image
my_selcet: select a mothod for converting
img: output image,it's a grayscale image
Description:
this function provides three methods for converting an image to a grayscale image:
(1)average. rgb=R/3+G/3+B/3
(2)max. rgb=max(R,G,B)
(3)weighted average. rgb=0.11*R+0.59*G+0.30*B
if my_select=1,then we use the first method to convert the image to a grayscale image
Example:
im = imread("lena.png");
img = col2gray(im,2);
16 bright - adjust
brightness of an image
Calling Sequence:
img = bright(im,rate)
Parmeters:
im: this is a MxNx3 unsigned char matrix(uint8).
rate: a value between -100 and 100,it shows the degree of brightness
img: a MxNx3 unsigned char matrix of output image
Description:
This function adjust brightness of an input image.If "rate" equals to 0,we'll not change the image's brightness.if rate<0,we get an image darker than input.The more ratio,the more brightness.
Example:
im = imread("lena.png");
img = brightness(im,25);
17. Blur- blur the image
Calling Sequence:
img = Blur(im)
Parmeters:
im: matrix of an input image
img: output image matrix
Description:
blur the image
Example:
im = imread("lena.png");
img = Blur(im);