Image Compression using Hierarchal Linear Polynomial Coding
Publication Date
Sat Jun 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Publication Date
Wed Jun 01 2022
Journal Name
V. International Scientific Congress Of Pure, Applied And Technological Sciences
Publication Date
Wed Jul 06 2022
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Publication Date
Wed Jul 25 2018
Journal Name
International Journal Of Engineering Trends And Technology
(1)
Publication Date
Thu Jun 01 2017
Journal Name
Iosr Journal Of Computer Engineering
Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Image Compression based on Adaptive Polynomial Coding of Hard & Soft Thresholding
Image compression
polynomial coding and hard and soft thresholding
In this paper, an adaptive polynomial compression technique is introduced of hard and soft thresholding of transformed residual image that efficiently exploited both the spatial and frequency domains, where the technique starts by applying the polynomial coding in the spatial domain and then followed by the frequency domain of discrete wavelet transform (DWT) that utilized to decompose the residual image of hard and soft thresholding base. The results showed the improvement of adaptive techniques compared to the traditional polynomial coding technique.
Publication Date
Wed Jul 25 2018
Journal Name
International Journal Of Engineering Trends And Technology
(1)
Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Speech Signal Compression Using Wavelet And Linear Predictive Coding
Keyword: Wavelet
Speech Coding
Linear Predictive Coding
Levinson Durbin.
A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th
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