X-Git-Url: http://www2.svjatoslav.eu/gitweb/?p=imagesqueeze.git;a=blobdiff_plain;f=doc%2Findex.html;h=4393fde39a1bb9feac6ae3ce2f946ef636e12e04;hp=7ccf9f68e8f25959e9b08704a1c436041c8809fa;hb=73cb3d304e28dbd4c44bbb0ba958f0439886da44;hpb=c7d0b8e1723045c0df086d9214a35f54db47684c diff --git a/doc/index.html b/doc/index.html old mode 100755 new mode 100644 index 7ccf9f6..4393fde --- a/doc/index.html +++ b/doc/index.html @@ -1,47 +1,386 @@ - - + + - -ImageSqueeze +ImageSqueeze - lossy image codec + + + + + + + + + + + -

ImageSqueeze - lossy image codec

- Download -    - Online homepage -    - Other applications hosted on svjatoslav.eu -
-Program author:
-    Svjatoslav Agejenko
-    Homepage: http://svjatoslav.eu
-    Email: svjatoslav@svjatoslav.eu
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ImageSqueeze - lossy image codec

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1 General

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-Lossy image codec. Optimized for photos. -I developed it to test out an image compression ideas. +
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1.1 Source code

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  • Download latest snapshot in TAR GZ format +
  • -I believe my algorithm has following advantages: - * Fast. Relatively few computations per pixel. - * Easy to add support for progressive image loading. (Saving is already progressive) +
  • Browse Git repository online +
  • -Current limitations / to do: - * Documentation describing idea behind this algorithm is still missing (lack of time) - * Code documentation is weak. - * Better sample applications needed: Commandline image conversion utility. Image viewer. +
  • Clone Git repository using command: +
    +git clone http://www2.svjatoslav.eu/git/imagesqueeze.git
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2 Overview

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

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

+I believe my algorighm has interesting advantages. +

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

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originalAndCompressed.png +

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+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. +

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3 Algorithm description

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3.1 Algorighm advantages

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  • It can be applied to any amount of dimensions, even for sound and +volumetric data. +
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  • Algorithm can operate in lossy and lossless mode. +
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  • 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. +
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  • Algorithm naturally supports variable resolution. That is: different +areas can be encoded with different resolutions / pixel densities. +
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  • Fast: Very little computations per pixel. +
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4 TODO Things to improve

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