Fixed Predictor Polynomial Coding for Image Compression
(1)
Publication Date
Sun Oct 01 2023
Journal Name
Int. J. Nonlinear Anal. Appl
Publication Date
Thu Jun 01 2017
Journal Name
International Journal Of Engineering Research And Advanced Technology
Publication Date
Sun Jul 01 2018
Journal Name
International Journal Of Engineering Research And Management
Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Publication Date
Fri May 16 2014
Journal Name
International Journal Of Computer Applications
(4)
Publication Date
Fri Dec 24 2021
Journal Name
Journal Of Engineering Science And Technology. Journal Of Engineering Science And Technology
(4)
Publication Date
Fri Nov 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Image Compression Using Tap 9/7 Wavelet Transform and Quadtree Coding Scheme
Image Compression
JPEG2000
Wavelet Transform Tap 9/7
Quadtree
LZW
This paper is concerned with the design and implementation of an image compression method based on biorthogonal tap-9/7 discrete wavelet transform (DWT) and quadtree coding method. As a first step the color correlation is handled using YUV color representation instead of RGB. Then, the chromatic sub-bands are downsampled, and the data of each color band is transformed using wavelet transform. The produced wavelet sub-bands are quantized using hierarchal scalar quantization method. The detail quantized coefficient is coded using quadtree coding followed by Lempel-Ziv-Welch (LZW) encoding. While the approximation coefficients are coded using delta coding followed by LZW encoding. The test results indicated that the compression results are com
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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Image Signal Decomposition Using Polynomial Representation with Hybrid Lossy and Non-Lossy Coding Scheme
Polynomial Representation
Image Compression
Discrete Cosine Transform
Run Length Coding
Quantization
This article presents a polynomial-based image compression scheme, which consists of using the color model (YUV) to represent color contents and using two-dimensional polynomial coding (first-order) with variable block size according to correlation between neighbor pixels. The residual part of the polynomial for all bands is analyzed into two parts, most important (big) part, and least important (small) parts. Due to the significant subjective importance of the big group; lossless compression (based on Run-Length spatial coding) is used to represent it. Furthermore, a lossy compression system scheme is utilized to approximately represent the small group; it is based on an error-limited adaptive coding system and using the transform codin
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(1)
Publication Date
Mon Mar 20 2023
Journal Name
2023 International Conference On Information Technology, Applied Mathematics And Statistics (icitams)