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High Efficient Image Compression Using Lempel-Ziv-Welch Algorithm


Affiliations
1 Velalar College of Engineering and Technology, India
2 Department of Electronics and Communication Engineering, Velalar College of Engineering and Technology, India
3 Department of Electronics and Communication Engineering, Velalar College of Engineering and Technology, India
     

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Nowadays, the multimedia applications faces several issues in the storage and transmission of image, video and audio data. This made the field of developing image compression methods necessary and vital. Image compression aims to reduce the redundancy of an image data. This paper introduces the concept of Lempel–Ziv–Welch (LZW) algorithm with Block Truncation method. LZW is a universal lossless algorithm for image compression which has the advantages of low computation load and less memory requirement. This algorithm is widely used in UNIX file and gif image format. This proposed technique is used to increase the Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR), and Mean Square Error (MSE).


Keywords

Block Truncation, Compression Ratio, Image Compression, LZW, MSE, PSNR.
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  • High Efficient Image Compression Using Lempel-Ziv-Welch Algorithm

Abstract Views: 134  |  PDF Views: 3

Authors

K. Rajeswari
Velalar College of Engineering and Technology, India
K. Kavitha
Department of Electronics and Communication Engineering, Velalar College of Engineering and Technology, India
G. Boopathi Raja
Department of Electronics and Communication Engineering, Velalar College of Engineering and Technology, India

Abstract


Nowadays, the multimedia applications faces several issues in the storage and transmission of image, video and audio data. This made the field of developing image compression methods necessary and vital. Image compression aims to reduce the redundancy of an image data. This paper introduces the concept of Lempel–Ziv–Welch (LZW) algorithm with Block Truncation method. LZW is a universal lossless algorithm for image compression which has the advantages of low computation load and less memory requirement. This algorithm is widely used in UNIX file and gif image format. This proposed technique is used to increase the Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR), and Mean Square Error (MSE).


Keywords


Block Truncation, Compression Ratio, Image Compression, LZW, MSE, PSNR.