Image resize image in matlab

Hi, I am facing a blurring issue in the below code:

I = imread('waterframe-1.png');

I=imresize(I,[16 16]);

I=rgb2ycbcr(I);

I=ycbcr2rgb(I);

I=imresize(I,[256 256]);

I=ycbcr2rgb(I);

imshow(I);

Any help in this will be very highly appreciated

Thanks Mehwish

[Jan]

You forgot to mention any dteilas about the problem. What exactly do you see and what do you expect?

Answer 1

[Benoît THOUY]

Hi,

When upsampling, you have to deal with interpolation in order to predict missing pixels. As you do not know all 256*256 pixels with only 16*16 pixels, it uses some kind of "averaging" closest pixels to compute all pixels.

imresize uses bilinear interpolation by default. You can change to bicubic interpolation to have more "sharp" edges, but it will be blurred anyway. Nearest-neighbor interpolation will give you a "block" effect so no blur but big [16 16] squares. It is up to your choice. See documentation of imresize: www.mathworks.com/help/images/ref/imresize.html

[Mehwish]

Thanks a lot. It clears up a lot of mess in my head.

Regards

Mehwish

Answer 2

[Chandra Shekhar]

dont resize original image to [16 16] make it as it is.

follow following code to get more info

I = imread('waterframe-1.png');

I=imresize(I,[256 256]);

I=rgb2ycbcr(I);

I=ycbcr2rgb(I);

I=imresize(I,[256 256]);

I=ycbcr2rgb(I);

figure;imshow(I);

Answer 3

[Mehwish]

Yup. I know it works. Thanks for the quick response. This is a short version of the algorithm which I am implementing. And the whole algorithm revolves around resizing the image to 16X16 and the conversion to ycbcr. So not resizing is out of question.

Answer 4

[Mehwish]

@ Jan I see blurring of the image and I expect to resolve it with some filter maybe....