It seems to me that usually dithering is done in time space. In case of PCM coding, it's comprehensible as the data is represented in time space. But what about transform coders? In our case we can access to both representations, time and frequency spaces. So I've had an idea. Perhaps it's full of nonsense, perhaps it needs to be corrected, in this case I'd like to be corrected in order to learn.
My idea is to use an adaptative dithering in frequency space. As in decoding we know how much bits were used in a sfb, we could perhaps use this data to adjust the amount of dithering. This way we could dither more when less bits were used, and dither less when more bits were used.
Any comments about this?
Regards,
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Gabriel Bouvigne - France bouvigne@mp3-tech.org mobile phone: gsm@mp3-tech.org icq: 12138873
MP3' Tech: www.mp3-tech.org
My idea is to use an adaptative dithering in frequency space. As in decoding we know how much bits were used in a sfb, we could perhaps use this data to adjust the amount of dithering. This way we could dither more when less bits were used, and dither less when more bits were used.
Hmm, an interesting idea.
In another forum I've tried to make the distinction between quantization noise introduced by the encoder (as part of the lossy psychoacoustic coding algorithm) and quantization noise introduced by the decoder (in the output PCM samples.) Dithering the output PCM only affects the latter.
I've been under the assumption the decoder has no control over the quantization noise introduced by the encoder. After all, the quantized bits are gone, so it's not possible to know what the error was, even knowing the number of bits in the quantized result. I'm not sure how you would apply dither in this case since there is nothing to dither from.
Perhaps frequency dithering could take place instead in the encoder, where the quantization error is known?
Other thoughts?
-rob
A second thought:
It might be possible to apply a "diffusion" to the quantized frequencies in the decoder, sort of like dither, but with the effect of treating all values within some window of the quantized value equally likely. The window could be larger for values quantized with fewer bits, and smaller for values with more bits.
It might make the sound worse; I don't know.
Maybe this is what you were thinking of, Gabriel? Is it worth trying?
-rob
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Gabriel Bouvigne -
Rob Leslie