Image Compression Using PCA and Improved Technique with MLP Neural Network

V Gaidhane; V Singh; M Kumar

doi:10.1109/ARTCom.2010.15

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Image Compression Using PCA and Improved Technique with MLP Neural Network

V Gaidhane, V Singh and M Kumar

2010 International Conference on Advances in Recent Technologies in Communication and Computing, pp.106-110

2010-10

DOI: https://doi.org/10.1109/ARTCom.2010.15

Abstract

Principle Component Analysis

Image coding

PSNR

Feed forward neural network

Neurons

Artificial neural networks

Image compression

Feeds

Pixel

Principal component analysis

Computer images consist of large data and hence require more space to store in the memory. The compressed image requires less storing space of memory and less time to transmit. In this paper, feed forward back propagation neural network method with PCA technique is used for image compression. It is found that the results using PCA techniques are not satisfactory. To improve these results author suggest another technique which has better results. The Artificial Neural Network (ANN) used in these technique is trained by considering the different numbers of hidden neurons, epoch and reconstructed image compared with original image.

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Title: Image Compression Using PCA and Improved Technique with MLP Neural Network
Creators: V Gaidhane - Dept. of Electron. & Commun., G.L.A Inst. of Technol. & Manage., Mathura, India
V Singh - ICE Div., N.S.I.T., New Delhi, India
M Kumar - U.P. Tech. Univ., Lucknow, India
Publication Details: 2010 International Conference on Advances in Recent Technologies in Communication and Computing, pp.106-110
Publisher: IEEE
Academic Unit: UMMG Dept of Psychiatry & Behavioral Sciences; Miller School of Medicine
Language: English
Resource Type: Conference proceeding
Record Identifier: 991031598394802976