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by klodolph
1223 days ago
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I’m guessing there’s just a lot left on the table— > Maybe values could be represented as 0..1, and the values itself could be stored as 0.16 fixed point numbers. Use some generic compression on top. Codecs like JPEG use a variable amount of quantization. You quantize by scaling the 0..1 float by some scalar, putting it in the range 0..k, and then truncating it to an integer, and encoding the integer. The integer value is encoded using an entropy coder like Huffman. The parameter k must also be encoded somehow, or fixed. Look up “JPEG coefficient quantization” for how JPEG does it. Codecs for audio and images are often made up of understandable parts that fit together: transformations, quantization, entropy coding. If you come up with a new transformation, you can make a whole codec by putting together the remaining pieces—but something like a new transformation is itself interesting, because somebody else can always assemble it into a codec if it shows promise. |
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The reason quantization works so well in JPEG is because of the DCT step and its energy compaction properties. This gets most of the coefficients near zero. I think without this transform you would be introducing a lot more noise in the final result.
At some point, we are going to end up re-implementing a thing approximating jpeg here. Colorspace convert, subsampling & DCT+quantization is most of the magic sauce.