Er. Ramandeep Kaur Grewal and Randhawa, N. (2012) Image Compression Using Discrete Cosine Transform & Discrete Wavelet Transform. Proceedings of “I-Society 2012” at GKU, Talwandi Sabo Bathinda (Punjab).
http://www.researchmanuscripts.com/index.php?option=com_content&view=article&id=67&Itemid= 76

has been cited by the following article:

• TITLE: Huffman Image Compression Incorporating DPCM and DWT

  AUTHORS: Mohamed Abo-Zahhad, Reda Ragab Gharieb, Sabah M. Ahmed, Mahmoud Khaled Abd-Ellah

  KEYWORDS: Medical Image Compression, Brain Image Compression, CT, DPCM, DWT, CR

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.6 No.2, April 24, 2015

  ABSTRACT: This paper presents a medical image compression approach. In this approach, first the image is preprocessed by Differential Pulse Code Modulator (DPCM), second, the output of the DPCM is wavelet transformed, and finally the Huffman encoding is applied to the resulting coefficients. Therefore, this approach provides theoretically threefold compression. Simulation results are presented to compare the performance of the proposed (DPCM-DWT-Huffman) approach with the performances of the Huffman incorporating DPCM (DPCM-Huffman), the DWT-Huffman and the Huffman encoding alone. Several quantitative indexes are computed to measure the performance of the four algorisms. The results show that the DPCM-DWT-Huffman, the DWT-Huffman, the DPCM-Huffman and the Huffman algorisms provide compression ratio (CR) of 6.4837, 4.32, 2.2751 and 1.235, respectively. The results also confirm that while the proposed DPCM-DWT-Huffman approach enhances the CR, it does not deteriorate other performance quantitative measures in comparison with the DWT-Huffman, the DPCM-Huffman and the Huffman algorisms.