## how to find existence of noise and edges in a color image using gradient?

Asked by ARUN SAI

### ARUN SAI (view profile)

on 26 May 2013

matlab code to find existence of noise and edges in a color image using gradient?

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### Image Analyst (view profile)

Answer by Image Analyst

### Image Analyst (view profile)

on 26 May 2013

Try subtracting the image from your noise-free version to get the noise. Then, have you tried to use imgradient? Or you could try a local delta E (color difference) as given in my demo code: http://www.mathworks.com/matlabcentral/answers/73741#comment_145951

ARUN SAI

### ARUN SAI (view profile)

on 26 May 2013

i have tried this code for finding the existence of noise and edges in a color image named as mandi.tif which is cfa raw image in the matlab library.

` for i=2:1:m-1`
`     for j=2:1:n-1`

% horizontal internal gradient

```A1=abs(r(i-1,j-1)-r(i+1,j+1));
```

% vertical internal gradient

```B1=abs(r(i-1,j+1)-r(i+1,j-1));
```
`    end`
` end`
` for i=3:1:m-2`
`    for j=3:1:n-2`

% horizontal external gradient

`      A2=abs(2*g(i,j)-g(i-1,j-2)-g(i+1,j+2)); `

% vertical external gradient

`      B2=abs(2*g(i,j)-g(i-2,j-1)-g(i+2,j+1)); `
```    end
end```

% to find existence of edge or influence of the noise TH (enumeration variable) is used for noise that in the up and down or in any point of g(i,j)

` for k=2:2:m-1`
`     for l=3:2:n-1`
`        x=[k-1,k+1];`
`        y=[l-1,l+1];`

%up says that g(i,j-1) is the noise

` up=(A1<B1)&(eq(A2,B2))&eq(max(abs(2*r(k,y)-r(k-1,l)-r(k+1,l))),l-1);    `

%down says that g(i,j+1) is the noise

` down=(A1<B1)&(eq(A2,B2))&eq(max(abs(2*r(k,y)-r(k-1,l)-r(k+1,l))),l+1); `

%left says that g(i-1,j) is the noise

` left=(A1>B1)&(eq(A2,B2))&eq(max(abs(2*r(x,l)-r(k,l-1)-r(k,l+1))),k-1);`

%right says that g(i+1,j) is the noise

` right=(A1>B1)&(eq(A2,B2))&eq(max(abs(2*r(x,l)-r(k,l-1)-r(k,l+1))),k+1);`

*%no says that there is no noise and also no edge *

` no=(eq(A1,B1))&(eq(A2,B2)); `

% level says that there is a edge in vertical direction

` level=(A1>B1)&(A2>B2); `

% erect says that there is a edge in horizontal direction

` erect=(A1>B1)&(A2<B2);`
`    end`
` end`
` p=[1 2 3 4 5 6 7]`
` TH=[up down left right no level erect]`
` p_TH=p(TH==1)`
` for i=2:1:m-1`
`    for j=2:1:n-1`

% switches according to the TH value switch p_TH

```    case 1
r(i,j)=(r(i-1,j)+r(i+1,j)+r(i,j+1))/3;
r(i,j-1)=r(i,j);```
```    case 2
r(i,j)=(r(i-1,j)+r(i+1,j)+r(i,j-1))/3;
r(i,j+1)=r(i,j);```
```    case 3
r(i,j)=(r(i+1,j)+r(i,j-1)+r(i,j+1))/3;
r(i-1,j)=r(i,j);```
```    case 4
r(i,j)=(r(i-1,j)+r(i,j-1)+r(i,j+1))/3;
r(i+1,j)=r(i,j);```
```    case 5
r(i,j)=(r(i-1,j)+r(i+1,j)+r(i,j-1)+r(i,j+1))/4;```
```    case 6
r(i,j)=(r(i-1,j)+r(i+1,j))/2;```
```    case 7
r(i,j)=(r(i,j-1)+r(i,j+1))/2;```
` end`
`    end`
` end`
` s=r+g+b;`
` figure,imshow(s);`

%signal to noise ratio calculation of image after removal of noise

` m3=mean2(s);`
` SD3=mean2(stdfilt(s));`
` snr3=(m3/SD3) `

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