Logic Gone - Save wavelets from MountainView Monster!

A Googlet was long known to refer to any company or entity snatched up by Google (do you really need a link here?). All logic gone*, Google Inc.* now plans a wavelet invasion on a much larger basis, with its new real-time communication platform. Let us have a quick look at Google Wave's (a complete guide) terminology:

• Wave: A wave, specifically, refers to a specific threaded conversation. It can include just one person, or it can include a group of users or even robots. [...] like your entire instant messaging (IM) history with someone. Anything you’ve ever discussed in a single chat or conversation is a wave.
• Wavelet: A wavelet is also a threaded conversation, but only a subset of a larger conversation (or a wave). It’s like a single IM conversation – a small part of a larger conversation and a larger history. Wavelets, though, can be created and managed separately from a wave (sic).
• Blip: Even smaller than a Wavelet, a Blip is a single, individual message. It’s like a single line of an IM conversation. Blips can have other blips attached to them, called children.
  

Something smaller than a wavelet? A waveletelet? Is this even at a tweet level? No kidding. And it is going further on Internet Explorer**. To grab its next territories from lone PC**. So expect online terrors from it**! And its name is Google... Frame. A much larger basis, told you. Not a nun Movie, wait***! But a minutia woven*** masterplan. Now let MountainView**** Monster, Google, furbish its Wavelet Munition****. But let us not become "le gogo" de Google. And let us celebrate in peace the Haar wavelet centenary in 2010.

Amongst the latest "WITS: Where is the Starlet" updates: loglets, steerlets and tetrolets. And a few new SIVA conferences such as MIA 2009 in Paris at very short sight.

WITS: Tetrolet wavelets

The WITS (and the Virtue) honors today tetrolets, a breed of Haar-type wavelet transform based on tetrominoes. The preprint: "Tetrolet Transform: A New Adaptive Haar Wavelet Algorithm for Sparse Image Representation", may be found at J. Krommweh page (or local copy). The abstract reads:

In order to get an efficient image representation we introduce a new adaptive Haar wavelet transform, called Tetrolet Transform. Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. The corresponding filter bank algorithm is simple but enormously effective. In every level of the filter bank algorithm we divide the low-pass image into 4 × 4 blocks. Then in each block we determine a local tetrolet basis which is adapted to the image geometry in this block. An analysis of the adaptivity costs leads to modified versions of our method. Numerical results show the strong efficiency of the tetrolet transform for image compression