looking 4 a wallpaper

Hi all, im looking for a wallpaper.

This is the thumb of the wallpaper that i want:


Looks like these ones:




but in white background and glossy 'M'.

Anyone got it, pliz??

Yeah, Im asking if someone have the little image as wallpaper (320x240, u know).

Its something wrong?

Originally Posted by alvin23

Yeah, Im asking if someone have the little image as wallpaper (320x240, u know).

Its something wrong?

I can propose you that :



It's not very clear but maybe it's what you want :D !

I think u have resized the little image i've posted.

Thx for the try xx-c, but i'm searching for a bigger image to resize it to 320x240.

Thx anyway.

xx-c, can I ask what method you used to resize the little image, if you did?

You got way better results than anything like normal bicubic or Lanczos resampling. You even eliminated the JPG artefacts!

Originally Posted by xx-c

I can propose you that :



It's not very clear but maybe it's what you want :D !

Originally Posted by member

xx-c, can I ask what method you used to resize the little image, if you did?

You got way better results than anything like normal bicubic or Lanczos resampling. You even eliminated the JPG artefacts!

I resized it, then used Photofiltre to : add the grey background because the picture wasn't 320x240, "boost" colors and clearness, and use "antipoussière" (i don't know the word in english) !

Originally Posted by xx-c

I resized it, then used Photofiltre to : add the grey background because the picture wasn't 320x240, "boost" colors and clearness, and use "antipoussière" (i don't know the word in english) !

Ah good tips! I think "antipoussière" might be "noise reduction" in english (although web translators give "dust protection"). I think this was probably the crucial step. Interesting! You did a careful job there.

Thanks!

No one have it??

it is beautiful
thank you very much

Originally Posted by member

xx-c, can I ask what method you used to resize the little image, if you did?

You got way better results than anything like normal bicubic or Lanczos resampling. You even eliminated the JPG artefacts!

If you look carefully theres still a little banding - probably resolved by the "noise reduction" (most likely a blurring filter, in this case atleast?). If your interested in that sort of thing though look for "super-resolution". The way I have seen this done involves fourier transforms:

• create a large image, spacing samples from the original image evenly accross it, all unknown values are black.
• iteratively:
  • transform to the fourier space (FT)
  • remove high frequency components (remove noise)
  • go back to image space (IFT)
  • reset the colour of known pixels to those from the known images (FT is known for adding a few unwanted effects when not used perfectly)
  • add another images samples, equally spaced (at an offset from all the previous locations used, but in roughly the same area) accross the large image.
  • repeat until your happy / have no more "unknown" values

It might be wrong, but thats what I read in my notes. You might also want to check out:
http://auricle.dyndns.org/ALE/ , they have some nice image restoration demos there.

Originally Posted by member

Ah good tips! I think "antipoussière" might be "noise reduction" in english (although web translators give "dust protection"). I think this was probably the crucial step. Interesting! You did a careful job there.

Thanks!

I use antipoussière around the house to keep the pussy in line. Go through umpteen cans of it in springtime.

I have a lot of wallpapers you can download at:
[Packeting Download]WallPapers For M6

How about these?

Originally Posted by b-w-d

If you look carefully theres still a little banding - probably resolved by the "noise reduction" (most likely a blurring filter, in this case atleast?). If your interested in that sort of thing though look for "super-resolution". The way I have seen this done involves fourier transforms:

• create a large image, spacing samples from the original image evenly accross it, all unknown values are black.
• iteratively:
  • transform to the fourier space (FT)
  • remove high frequency components (remove noise)
  • go back to image space (IFT)
  • reset the colour of known pixels to those from the known images (FT is known for adding a few unwanted effects when not used perfectly)
  • add another images samples, equally spaced (at an offset from all the previous locations used, but in roughly the same area) accross the large image.
  • repeat until your happy / have no more "unknown" values

It might be wrong, but thats what I read in my notes. You might also want to check out:
http://auricle.dyndns.org/ALE/ , they have some nice image restoration demos there.

That's a great reply! Thanks for the Fourier explanation there!

BTW, is that banding or the posterization from the original image? (but I may not be looking in the right place, probably).

The results in those links are astonishing. I thought I already knew what was possible, with the NoiseNinja, PictureCooler et al. generation of programs. These ones you show seem to be a whole new class, if I'm not mistaken.
EDIT: oh, I just saw that the example on the Wikipedia page actually uses data from 9 images to scale up the resolution... so "super-resolution" always uses data from more than one image, I take it?

Originally Posted by kiloscott

I use antipoussière around the house to keep the pussy in line. Go through umpteen cans of it in springtime.

:D

I know what you mean about spring... I hear it has side-effects though, so I'm trying to give up drinking the stuff.

So?? no one got this image as original?

Originally Posted by member

.. Thanks
...
BTW, is that banding or the posterization from the original image? (but I may not be looking in the right place, probably).
...
EDIT: oh, I just saw that the example on the Wikipedia page actually uses data from 9 images to scale up the resolution... so "super-resolution" always uses data from more than one image, I take it?

Your welcome, feel free to message me so we dont clutter this thread up any more.

Now you mention it im not sure, could easily be original posterization. Yes super-resolution tends to use more than 1 image but as it says on wiki "There are both single-frame and multiple-frame variants of SR, where multiple-frame are the most useful". Its nice that image processing is still an area of ongoing research :D

[Dont mean to hijack the thread, sorry ]