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ijs-5081
Image Compression Using Mapping Transform with Pixel Elimination
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     In today's world, digital image storage and transmission play an essential role,where images are mainly involved in data transfer. Digital images usually take large storage space and bandwidth for transmission, so image compression is important in data communication. This paper discusses a unique and novel lossy image compression approach. Exactly 50% of image pixels are encoded, and other 50% pixels are excluded. The method uses a block approach. Pixels of the block are transformed with a novel transform. Pixel nibbles are mapped as a single bit in a transform table generating more zeros, which helps achieve compression. Later, inverse transform is applied in reconstruction, and a single bit value from the table is remapped into pixel nibbles. With these nibbles, pixel values of the block are reconstructed without any loss. The average method is used in reconstruction of excluded pixels. This approach achieves better quality in reconstructed test images at lower PSNR values ranging from 33dB to 44dB. Compression ratio achieved is more than 2. Correctness ratio achieved by proposed method is more than 0.5.

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Publication Date
Sun Jan 01 2023
Journal Name
Proceedings Of International Conference On Data Science And Applications
Very Low Illumination Image Enhancement via Lightness Mapping
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Publication Date
Mon Jun 01 2015
Journal Name
. International Journal Of Computer Science And Mobile Computing
A Hybrid Lossy Image Compression based on Wavelet Transform, Polynomial Approximation Model, Bit Plane Slicing and Absolute Moment Block Truncation
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Publication Date
Sun Jan 01 2023
Journal Name
2nd International Conference On Mathematical Techniques And Applications: Icmta2021
Polynomial image compression: A review
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Publication Date
Wed Nov 27 2019
Journal Name
Iraqi Journal Of Science
Bit Plane Slicing, Wavelet and Polynomials Mixing for Image Compression
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     This paper introduced a hybrid technique for lossless image compression of natural and medical images; it is based on integrating the bit plane slicing and Wavelet transform along with a mixed polynomial of linear and non linear base. The experiments showed high compression performance with fully grunted reconstruction.

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Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values
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Publication Date
Thu Nov 29 2018
Journal Name
Iraqi Journal Of Science
Application of WDR Technique with different Wavelet Codecs for Image Compression
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FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

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Publication Date
Sun Jun 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Artificial Neural Network for TIFF Image Compression
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The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256)  in our research, compressed them by using MLP for each

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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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Publication Date
Fri Apr 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Lossless and Lossy Polynomial Image Compression
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Publication Date
Fri Apr 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Lossless and Lossy Polynomial Image Compression
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