Re: Improving the quality of a blocky image

On Jun 9, 3:36 pm, Industrial One <industrial_...@xxxxxxxxxxx> wrote:
On Jun 9, 6:05 am, AJ <arandal...@xxxxxxxxx> wrote:> Hi All,

http://img222.imageshack.us/my.php?image=degradedimagesh2.png) and

Hawt.

I understand that the image is of such a poor quality that I do not
expect any huge improvements - that is not my aim, my aim is to see if
it can be improved at all, and if so, which method(s) could yield the
best results.

Probably a bi-cubic interpolation engine, which blends pixels together
at the simplest. The more complex processes involve detecting curves,
linear shapes/luminescence patterns and restores some quality in
accordance with aforementioned characteristics.

So far I have tried some iterative restoration techniques such as
Richardson-Lucy deconvolution and Blind deconvolution - both have
proved to give a slight improvement.

I was hoping someone would have some other suggestions as to how I
could possibly improve the image.

There's only so much information you can "guess back" when you've
trashed a portion of it. If I ripped out every 5th letter of this
message, you'd probably be able to guess the missing characters 'cuz
you still have a majority of existing info, but if I took out every
2nd letter... some words you could restore, most you can't cuz they
got multiple possibilities, your picture would be equal to something
like that.

Just in case understanding how the image was degraded in the first
place might help lead to a good suggestion for improvement algorithms,
I created the image using the following steps:

* 8x8 Sub-Block and DCT image
* store top 2 coefficients from each sub-block
* use these to create a new image

Many thanks,

AJ

DCT is beyond me. But your image was degraded by a lossy algorithm --
irreversible. Information was lost, plain and simple.

Just pay an experienced photoshop user to restore your picture by hand.

Thanks for your reply.

Paying an experienced photshop user is not really an option...I have a
copy of the original image, I would just use that if that was my aim.
What I am trying to do is restore this poor image as much as possible
before finally using it as a form of highly compressed restoration
data if portions of the original image are degraded.

Good suggestion with the interpoliation. I have just experimented
with that and have got some reasonable results.
After some iterative restoration and interpolation, the image is
looking quite a lot better :) Do you have any suggested algorithms/
techniques I could try and apply to fix the edges (which seem to be
the worst regions of the image). Possibly some kind of edge
detection, followed by a filter to blur only the selected regions? I
am currently experimenting in Matlab if that makes any difference
(maybe there are already some implemented functions to complete this
task? I have had a google but couldn't find anything...).

Many thanks,

AJ
.

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