sir i have written the code for removing the noise in a color image.so can it be extended for video file

 i = imread('mandi.tif');

 imshow(i);

%demosaic of image

 rgb = demosaic(i,'bggr'); *%raw image is converted into true color image*

 figure,imshow(rgb);

 m1=mean2(rgb);

 SD1=mean2(stdfilt(rgb));

 snr1=(m1/SD1) *%signal to noise ratio calculation of noise free image*

 for i=500:1:1000

    for j=500:1:1000

        rgb(i,j)=imnoise(rgb(i,j),'gaussian',9); *%noise addition*

    end

 end
 figure,imshow(rgb);

 m2=mean2(rgb);

 SD2=mean2(stdfilt(rgb));

 snr2=(m2/SD2) *%signal to noise ratio calculation of noisy image*

 r=rgb;g=rgb;b=rgb;

 r(:,:,2)=0;
 r(:,:,3)=0;  

 g(:,:,1)=0;
 g(:,:,3)=0;

 b(:,:,1)=0;
 b(:,:,2)=0;

 m = size(rgb,1) 
 n = size(rgb,2)

 for i=2:1:m-1

     for j=2:1:n-1

 A1=abs(r(i-1,j-1)-r(i+1,j+1)); *% horizontal internal gradient*

 B1=abs(r(i-1,j+1)-r(i+1,j-1)); *% vertical internal gradient*

    end

 end

 for i=3:1:m-2

    for j=3:1:n-2

      A2=abs(2*g(i,j)-g(i-1,j-2)-g(i+1,j+2)); *% horizontal external gradient*

      B2=abs(2*g(i,j)-g(i-2,j-1)-g(i+2,j+1)); *% vertical external gradient*

    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=(A1<B1) & (eq(A2,B2)) & eq(max(abs(2*r(k,y)-r(k-1,l)-r(k+1,l))),l-1); %up 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); %down says that g(i,j+1) 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); %left 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); %right says that g(i+1,j) is the noise

no=(eq(A1,B1)) & (eq(A2,B2)); *%no says that there is no noise and also no edge *

level=(A1>B1) & (A2>B2); % level says that there is a edge in vertical direction

erect=(A1>B1) & (A2<B2); % erect says that there is a edge in horizontal direction

    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);

 m3=mean2(s);

 SD3=mean2(stdfilt(s));

 snr3=(m3/SD3) *%signal to noise ratio calculation of image after removal of  noise*