To Improvement in Image Compression ratio using Artificial Neural Network Technique

Authors

  • Ahmad S Bhagwant University, Ajmer

Keywords:

Neural Network, Data Compression, Image Compression, ANN

Abstract

Compression of data in any form is a large and active field as well as a big business. This paper presents a neural network based technique that may be applied to data compression. This paper breaks down large images into smaller windows and eliminates redundant information. Finally, the technique uses a neural network trained by direct solution methods. Conventional techniques such as Huffman coding and the Shannon Fano method, LZ Method, Run Length Method, LZ-77 are discussed as well as more recent methods for the compression of data presents a neural network based technique that may be applied to data compression. The proposed technique and images. Intelligent methods for data compression are reviewed including the use of Back propagation and Kohonen neural networks. The proposed technique has been implemented in C on the SP2 and tested on digital mammograms and other images. The results obtained are presented in this paper.

References

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Published

2024-02-26

How to Cite

Ahmad, S. (2024). To Improvement in Image Compression ratio using Artificial Neural Network Technique. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(01). Retrieved from https://ijact.in/index.php/j/article/view/91

Issue

Section

Original Research Article

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