how to make smooth and remove the white edge? Besides, why the black lines arise in my answer? How to solve it? - image

Question

Based on Shai and Biguri's codes and comments, I have finished a color picture like this:
A problem arises, how to remove the white edge and make it smooth? One solution may be to build 3x3 matrix or bigger and average. But the calculations should be large for every white-edge points. Or there may be some useful functions in Matlab to deal well with this problems?

Answer 1

If you have a license for the image processing toolbox, you can try using for example medfilt2 to apply a median filter on the image. A 11 by 11 median filter should do the trick. It is not very difficult to reimplement the filter yourself if you don't have the toolbox.
This is just one of the possibilities, you can use many different filters that will have different impacts on sharpness ang edge removal.
Edit:
Here is a quick median filter implementation (it may contain errors and could be optimized):
function ret = imageMedianFilter(im, np)
if(size(np,2) == 1)
npx = np;
npy = np;
else
npx = np(1);
npy = np(2);
end
ret = zeros(size(im,1),size(im,2));
for xpos = 1:size(im,1)
for ypos = 1:size(im,2)
curval = double(0);
if(xpos + npx - 1) > size(im,1)
npixels_x = size(im,1) - xpos + 1;
else
npixels_x = npx;
end
if(ypos + npy - 1) > size(im,2)
npixels_y = size(im,2) - ypos + 1;
else
npixels_y = npy;
end
a = im(xpos:xpos+npixels_x-1 , ypos:ypos+npixels_y-1);
a = reshape(a,1,size(a,1)*size(a,2));
curval = median(a);
ret(xpos , ypos) = curval;
end
end
ret = uint8(ret);
end
You can use it on R,G and B components as shown by Rotem below:
RGB = cat(3, imageMedianFilter(RGB(:,:,1), [11,11]), imageMedianFilter(RGB(:,:,2), [11,11]), imageMedianFilter(RGB(:,:,3), [11,11]));
(assuming your image is named RGB).

Answer 2

Here is my solution. I take n*n patch to average the near RGB. But there is a problem arising. Why the right down side of processed picture showing black lines?
clc;clf;close all;clear all;
img = imread('sample2color_t1.bmp'); %// read image
bw = img(:,:,1) > 128; %// convert to binary mask
[lb,lab] = bwlabel(bw,4); %// extract distinct regions
[a,b,c]=size(img);
R=ones(a,b);
G=ones(a,b);
B=ones(a,b);
%I have omitted other colors process codes. Below it is the white edges code.
r=[];c=[];
[r,c] = find(lb ==0);
for i=1:length(r)
R(r(i),c(i))=1;
G(r(i),c(i))=1;
B(r(i),c(i))=1;
end
scale=5;%步长1,8连通
for i=1:length(r)
sumR=0;sumG=0;sumB=0;
for j=0:2*scale
for k=0:2*scale
sumR=sumR+R(r(i)-scale+j,c(i)-scale+k);
sumG=sumG+G(r(i)-scale+j,c(i)-scale+k);
sumB=sumB+B(r(i)-scale+j,c(i)-scale+k);
end
end
R(r(i),c(i))=sumR/(2*scale+1)^2;
G(r(i),c(i))=sumG/(2*scale+1)^2;
B(r(i),c(i))=sumB/(2*scale+1)^2;
end
imPaint=cat(3,R,G,B);
figure;
imshow(imPaint);