#+TITLE: ImageSqueeze - lossy image codec
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* General

- This program is free software: you can redistribute it and/or modify
  it under the terms of the [[https://www.gnu.org/licenses/lgpl.html][GNU Lesser General Public License]] as
  published by the Free Software Foundation, either version 3 of the
  License, or (at your option) any later version.

- Program author:
  - Svjatoslav Agejenko
  - Homepage: http://svjatoslav.eu
  - Email: mailto://svjatoslav@svjatoslav.eu

- [[http://www.svjatoslav.eu/projects/][Other software projects hosted at svjatoslav.eu]]

** Source code
- [[http://www2.svjatoslav.eu/gitweb/?p=imagesqueeze.git;a=snapshot;h=HEAD;sf=tgz][Download latest snapshot in TAR GZ format]]

- [[http://www2.svjatoslav.eu/gitweb/?p=imagesqueeze.git;a=summary][Browse Git repository online]]

- Clone Git repository using command:
  : git clone http://www2.svjatoslav.eu/git/imagesqueeze.git

* Overview
Lossy image codec. Optimized for photos. I developed it to test out an
image compression ideas.

I believe my [[id:1d917f74-e763-4a71-976e-4aa60732efa6][algorighm has interesting advantages.]]

Below are original photo and the same image being compressed down to
~93 Kb and then decompressed.

[[file:originalAndCompressed.png][file:originalAndCompressed.png]]

When looking very closely, slight grainyness, loss of color precision
and blurriness (loss of detail) could be noticed as a compression
artifacts. Still sharp edges are always preserved. Also no blocks
typical to JPEG are ever seen.  I think that is awesome result for
just ~ 2.5 bits per pixel on that color photo.
* Algorithm description
+ Color image is split into three separate channels: Y, U and V.
  + Each channel is independently compressed.

+ Single channel compression method:

  + Algorithm is inspired by [[https://en.wikipedia.org/wiki/Diamond-square_algorithm][diamond-square algorithm]] that is meant to
    produce random heightmap/plasma effect.

  + During image compression: 2D image surface is iterated in the
    similar manner to diamond-square algorithm. Average color from
    neighbors is calculated and difference between neighbors average
    and actual pixel color is saved. As the pixel grid becomes
    gradually more dense, difference between neighbors tends to get
    smaller, thereby requiring less bits per pixel for storing the
    difference.
** Algorighm advantages
   :PROPERTIES:
   :ID:       1d917f74-e763-4a71-976e-4aa60732efa6
   :END:
+ It can be applied to any amount of dimensions, even for sound and
  volumetric data.

+ Algorithm can operate in lossy and lossless mode.

+ Algorithm naturally handles progressive loading. That is: low
  resolution thumbnail of entire thing is immediately available and
  gets gradually more dense during entire loading process.

+ Algorithm naturally supports variable resolution. That is: different
  areas can be encoded with different resolutions / pixel densities.

+ Fast: Very little computations per pixel.

* TODO Things to improve
- Code documentation is weak.

- Better sample applications needed:
  - Commandline image conversion utility.
  - Image viewer.

- Add lossless support.

- Extract algorithm key parts into reusable library and make it
  variable dimensional. So that the same code can be used for sound,
  image and volumetric data compression/decompression.