Image Compression Technique using Two Dimensional Discrete Cosine Transform
S. Rajeswari1, P. Deepthi2, K. V. Ramana Rao3
1S. Rajeswari, M.Tech Ece, Department, JNTU Kakinada University, Pydah College of Engineering and Tehnology, Visakhapatnam, India.
2P. Deepthi, Asst. Professor ,Dept. of Ece, Pydah College of Engineering & Technology, India.
3K.V. Ramana Rao, Assoc. Professor & Head, Dept. of ECE, Pydah College of Engineering & Technology, India.
Manuscript received on October 01, 2012. | Revised Manuscript received on October 20, 2012. | Manuscript Published on September 10, 2012. | PP: 56-59 | Volume-1 Issue-4, September 2012. | Retrieval Number: D0251081412/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents an architecture for the fast computation of the 8×8 two dimensional (2D) Inverse Discrete Cosine Transform. The proposed method is the permanent storage of the Basis Matrices of the 8×8 2D Discrete Cosine Transform (DCT). The sparseness property of the 2D DCT coefficient matrix, the computational time decreases as the number of nonzero coefficients decreases. The proposed structure computes all 64 pixel luminance values of an 8×8 block simultaneously. The design was implemented in Xilinx Xc3s500 board and the design used 23% LUT’s and 33% of the total slices. The total power consumed by the device was 0.081W.
Keywords: 2D IDCT, Image Processing, Sparse Matrices.