Lossless Image Compression using Differential Pulse Code Modulation and Its Purpose

2015 ◽  
Vol 8 (9) ◽  
pp. 249-256
Author(s):  
Rime Raj Singh Tomar ◽  
Kapil Jain
Keyword(s):  
Image Compression ◽  
Differential Pulse ◽  
Pulse Code Modulation ◽  
Lossless Image Compression ◽  
Differential Pulse Code Modulation ◽  
Code Modulation

scholarly journals A hybrid predictive technique for lossless image compression

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
N. A. N. Azman ◽  
Samura Ali ◽  
Rozeha A. Rashid ◽  
Faiz Asraf Saparudin ◽  
Mohd Adib Sarijari
Keyword(s):  
Image Compression ◽  
Data Storage ◽  
Image Data ◽  
Differential Pulse ◽  
Image Size ◽  
Pulse Code Modulation ◽  
Huge Amount ◽  
Transmission Bandwidth ◽  
Lossless Image Compression ◽  
Differential Pulse Code Modulation

Compression of images is of great interest in applications where efficiency with respect to data storage or transmission bandwidth is sought.The rapid growth of social media and digital networks have given rise to huge amount of image data being accessed and exchanged daily. However, the larger the image size, the longer it takes to transmit and archive. In other words, high quality images require huge amount of transmission bandwidth and storage space. Suitable image compression can help in reducing the image size and improving transmission speed. Lossless image compression is especially crucial in fields such as remote sensing healthcare network, security and military applications as the quality of images needs to be maintained to avoid any errors during analysis or diagnosis. In this paper, a hybrid prediction lossless image compression algorithm is proposed to address these issues. The algorithm is achieved by combining predictive Differential Pulse Code Modulation (DPCM) and Integer Wavelet Transform (IWT). Entropy and compression ratio calculation are used to analyze the performance of the designed coding. The analysis shows that the best hybrid predictive algorithm is the sequence of DPCM-IWT-Huffman which has bits sizes reduced by 36%, 48%, 34% and 13% for tested images of Lena, Cameraman, Pepper and Baboon, respectively.

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