The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 53-185
Full Name: Ranjan Senapati
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: A 306, SSB Hall of Residence, NIT Rourkela, Dist- Sundergarh, Orissa
Country: INDIA
Tel: 0661
Tel prefix: 2464461
Fax:
E-mail address: ranjankumarsenapati@gmail.com
Other E-mails: rksphd@gmail.com, senapatir@nitrkl.ac.in
Title of the Paper: A Fast Zigzag-Pruned 4×4 DTT Algorithm for Image Compression
Authors as they appear in the Paper: Ranjan Senapati, Umesh Pati, Kamala Mahapatra
Email addresses of all the authors: ranjankumarsenapati@gmail.com, ucpati@nitrkl.ac.in, kkm@nitrkl.ac.in
Number of paper pages: 10
Abstract: The Discrete Tchebichef Transform (DTT) is a linear orthogonal transform which has higher energy compactness property like other orthogonal transform such as Discrete Cosine Transform (DCT). It is recently found applications in image analysis and compression. This paper proposes a new approach of fast zigzag pruning algorithm of 4x4 DTT coefficients. The principal idea of the proposed algorithm is to make use of the distributed arithmetic and symmetry property of 2-D DTT, which combines the similar terms of the pruned output. Normalization of each coefficient is done by merging the multiplication terms with the quantization matrix so as to reduce the computation. Equal number of zigzag pruned coefficients and block pruned coefficients are used for comparison to test the efficiency of our algorithm. Experimental method shows that our method is competitive with the block pruned method. Specifically for 3x3 block pruned case, our method provides lesser computational c!
omplexity and has higher peak signal to noise ratio (PSNR). The proposed method is implemented on a Xilinx XC2VP30 FPGA to show its efficient use of hardware resources.
Keywords: Discrete Cosine Transform, Discrete Tchebichef Transform, Image compression, Peak signal to noise ratio, Zigzag Prune.
EXTENSION of the file: .pdf
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How Did you learn about congress: Image Compression
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