POCS and Color Spaces

31/08/2010

If you’re doing image processing, you’ve probably had to transform your image from one color space to another. In video coding, for example, the RGB image is transformed into YPrPb or YCrCb so that most of the visually relevant information is packed into the Y component which is essentially brightness. Subsampling the chroma bands (Cr and Cb) provides additional means for compression with little perceptual quality loss. While the human eye is very good at detecting brightness variation, it’s not very good at detecting subtle changes in chroma, either saturation or hue.

The thing is that very often, there are color space transformation matrices found in text book but they’re not, due to rounding (and other possible errors), always exactly inverses of each other. This week, I will discuss how we can use projections onto convex sets (POCS) to make sure that reduced precision matrices are exactly (within a given precision) reversible.

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More frobnulated Words

24/08/2010

In a previous post, I presented a couple of nonce and other frobnulated words.

Let us obstreperously add a few new words to the previous list.

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Or a Whale, II

17/08/2010

Tomorrow’s flowers are in the seeds of today.

Chinese proverb

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CodeNinja, desu yo!

16/08/2010


Or a Whale.

10/08/2010

HAMLET:
   Do you see yonder cloud that’s almost in shape of a camel?

POLONIUS:
   By the mass, and ’tis like a camel, indeed.

HAMLET:
   Methinks it is like a weasel.

POLONIUS:
   It is backed like a weasel.

HAMLET:
   Or like a whale.

POLONIUS:
   Very like a whale.

Hamlet, Act III

William Shakespeare

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2nd Year in Blogging

08/08/2010

I have just completed another year in blogging without missing a single scheduled post: This one is the 176th already!

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Wait… what?!

08/08/2010

What kind of stupid picture is that for a web site like 3GPP?


Rediscovering The Past

03/08/2010

Progress, as conceived by most people, consists in replacing older objects, techniques, or philosophies by newer, better, ones. Sometimes indeed the change is for the better, but sometimes it is just change for change—ever had an older device of some sort that was perfectly adequate for your usage, yet you still replaced it with a newer version with no net gain? Unfortunately, the same happens with ideas, especially with mathematics and computer science.

But there are lessons to be learnt from the past. I’m not talking about fables and cautionary tales; I’m talking about the huge body of science that was left behind, forgotten, superseded by modern techniques.

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