Signal Processing Stack Exchange
Signal Processing Stack Exchange

Questions tagged [compression]

This is for reducing the amount of data required to store a signal, whether lossy or lossless.

https://en.wikipedia.org/wiki/Data_compression

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How does adaptive Huffman coding work?

Huffman coding is a widely used method of entropy coding used for data compression. It assumes that we have complete knowledge of a signal's statistics. However, there are versions of Huffman coding that are used with streaming media and cannot…
Phonon
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Filtered Signal vs File Compression Paradox

1. Original Situation I have an original signal as a column data matrix n channels data x:mxn (single), with m=120019 the numer of samples and n=15 the number of channels. Also, i have the filtered signal as a filtered column data matrix x:mxn…
Brethlosze
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Compressive Sensing vs. Sparse Coding

There apparently are different terminologies used to refer to the same field called "compressive sensing" such as (see this wiki page): compressed sensing, compressive sampling, or sparse sampling. I wonder about "sparse sensing"…
Learn_and_Share
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References on the MP3 encoding algorithm

Does anybody have a reference describing the MP3 algorithm in a step-by-step manner and clear to understand? These references were a little bit confusing: Audio compression using modified discrete cosine transform,The MP3 Coding Standard,…
ali ha
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Theory behind Linear Predictive Coding (LPC)

What is the theory behind LPC? Why are(were) certain implementations of LPC said to be more tolerant of transmission or encoding errors quantization than other compressed voice encoding schemes? Can LPC methods also be used for smoothing or…
hotpaw2
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Speech Compression - In LPC how does the linear predictive filter work on a general level?

Hi I'm taking a multimedia systems course and I'm preparing for my exam on tuesday. I'm trying to get my head around LPC compression on a general level, but I'm having trouble with what is going on with the linear predictive filter part. This is…
user1058210
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What are some typical lossless compression ratios?

A client was trying to send me 250 GB worth of files. After attempting various ways of sharing the data, he sent me a zipped folder only 4 GB in size. That sounds like too much compression to me--I don't think when I've zipped things I've ever…
isomorphismes
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$8 \times 8$ block matrix in JPEG image compression?

In standard JPEG format of an image, Discrete Cosine transform is used. But instead of applying the transform on whole image, we first divide the image in $8 \times 8$ block and apply transform on each of them. Thus during quantization we remove…
Virange
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Difference between jpg compression and mp3 compression

My understanding of jpg compression is that, if done repeatedly, any image will eventually be reduced to a single flat color, due to the way it deals with neighboring pixels. However, years ago I was told that mp3 does not have this problem, a…
qwalter
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Error bounds in signal compression represented by truncated Moore-Penrose biorthogonal bases using von Neumann wavelets

I was reading and trying to reproduce the results in the arXiv preprint of Periodic Gabor Functions with Biorthogonal Exchange: A Highly Accurate and Efficient Method for Signal Compression by Asaf Shimshovitz et al., and a few questions arose. In…
DumpsterDoofus
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Non-orthogonal basis which offers better energy compaction in image compression

I am aware of image-independent basis, i.e. DCT, and image-dependent basis, i.e. Karhunen–Loève, which are used in compacting energies for image compression. These bases are orthorgonal. Are there any compression basis which are non-orthogonal that…
Ang Zhi Ping
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Compress a signal by storing signal diff instead of actual samples - is there such a thing?

I am working with EMG signals sampled at 2kHz and 16 bits, and noticed that they "look smooth", that is, the signals are differentiable, and if I apply a "diff" function (numpy.diff in my case) the magnitude of the values is considerably lower than…
heltonbiker
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What distribution is the easiest to compress?

I'm currently playing around with some compression algorithms and I'm asking myself if there is a type of data distribution / noise distribution that is easier to target with quantization (meaning less distortions at same rate). To my understanding…
Jane Dough
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Compression algorithms specific to complex signals

I am looking for (lossy or lossless) compression algorithms dedicated to complex signals. The latter could be composite data (like the left and right for stereo audio), a Fourier transformation or an intermediate step of a complex processing, an…
Laurent Duval
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Exam Question - end-to-end delay from video capture to video playout

Hi I'm preparing for my exam tomorrow and I've come across a 17 Mark question which seems trivially easy, so I think I'm missing a key point giving the rest of this exam is fairly difficult. The question is below and my attempt is below…
user1058210
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