Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding
Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
Color Image Denoising Using Stationary Wavelet Transform and Adaptive Wiener Filter
Stationary wavelet transform (SWT)
Adaptive Wiener filter
Thresholding
The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing. Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin
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Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
Image compression
Convolutional Autoencoder (CAE)
k-mean algorithm
PSNR
Compression Rate (CR)
MSE
Clustering
CLIC
Kodak
deep learning
lossy
Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
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Fri Dec 24 2021
Journal Name
Journal Of Engineering Science And Technology. Journal Of Engineering Science And Technology
(5)
Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Publication Date
Sun Oct 01 2023
Journal Name
Int. J. Nonlinear Anal. Appl
Publication Date
Fri Sep 01 2017
Journal Name
International Journal Of Engineering Research And Advanced Technology
Publication Date
Fri May 16 2014
Journal Name
International Journal Of Computer Applications
(4)
Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Speech Compression Using Multecirculerletet Transform
Sound
Speech Compression
MCT
DWT
Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp
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Fri Nov 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing