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Title: image compression using burrows wheeler transform matlab codes
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Title: vhdl code for image compression using discrete wavelet transform
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Title: image compression coding for hadamard transform using matlab
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Title: Image Transform Compression Using Wavelet
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Title: hybrid color image compression technique by using discrete wavelet transform and discrete cosine transform
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Title: Audio Compression Using a Munich and Cambridge Morlet Wavelet
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Created at: Thursday 28th of October 2010 07:24:27 PM
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Audio Compression Using a Munich and Cambridge Morlet Wavelet

khalil Abid and Kais Ouni
Laboratory of Systems and Signal Processing (LSTS)
National Engineering School of Tunis
ENIT, BP 37, Le Belv´edere 1002, Tunis, Tunisia



Abstract—

Most psycho-acoustic models for coding applications
use a uniform (equal bandwidth) spectral decomposition
as a first step to approximate the frequency selectivity of the
human auditory system. However, the equal filter properties
of the uniform sub- b ....etc

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Title: Feature Extraction for Audio Fingerprinting Using Wavelet Transform
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Posted By: seminar class
Created at: Wednesday 16th of February 2011 01:14:01 PM
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Absract
This paper proposes a novel feature extractionscheme for audio fingerprinting using discretewavelet transform (DWT). The proposed schemereduces the granularity, i.e., the minimal length ofaudio, needed for identification in an audiofingerprinting system. The scheme first decomposesthe video frame into sub-bands by DWT
The proposed scheme hastwo advantages:
(1) it needs smaller fingerprintgranularity than other previous work;
(2) it is notonly reliable but also robust against various signal
degradations according to the ex ....etc

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Title: matlab code for image compression using 2d dual tree discrete wavelet transform
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Created at: Tuesday 28th of May 2013 01:42:53 PM
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Title: IMAGE COMPRESSION USING DISCRETE COSINE TRANSFORM
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Posted By: seminar class
Created at: Wednesday 20th of April 2011 12:29:28 PM
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Submitted by
Nancy Singal


ABSTRACT
Image Compression addresses the problem of reducing the amount of data required to represent the digital image. Compression is achieved by the removal of one or more of
three basic data redundancies: (1) Coding redundancy, which is present when less than optimal (i.e. the smallest length) code words are used; (2) Interpixel redundancy, which results from correlations between the pixels of an image & (3) psycho visual redundancy which is due to data that is ignored by the ....etc

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