Adaptive segmentation of radar return and hybrid coding scheme

Xue Jianru; Zheng Nanning; Quan Wei

Volume 25 Issue 8

Aug. 2003

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2003 > 25(8): 1059-1065

Xue Jianru, Zheng Nanning, Quan Wei. Adaptive segmentation of radar return and hybrid coding scheme[J]. Journal of Electronics & Information Technology, 2003, 25(8): 1059-1065.

Citation:

Xue Jianru, Zheng Nanning, Quan Wei. Adaptive segmentation of radar return and hybrid coding scheme[J]. Journal of Electronics & Information Technology, 2003, 25(8): 1059-1065.

Xue Jianru, Zheng Nanning, Quan Wei. Adaptive segmentation of radar return and hybrid coding scheme[J]. Journal of Electronics & Information Technology, 2003, 25(8): 1059-1065.

Citation:

Xue Jianru, Zheng Nanning, Quan Wei. Adaptive segmentation of radar return and hybrid coding scheme[J]. Journal of Electronics & Information Technology, 2003, 25(8): 1059-1065.

PDF( 867 KB)

Adaptive segmentation of radar return and hybrid coding scheme

Received Date: 2002-03-15
Rev Recd Date: 2002-09-23
Publish Date: 2003-08-19

Abstract

Abstract

In this paper, an adaptive segmentating, hybrid coding scheme of radar return is presented. Firstly, radar return is divided into two classes by adaptive Gaussian mixture model: foreground and background, the former is composed of moving targets, while the later is composed of still objects and repeat motion. Then Integer-to-integer wavelet transform is used for de-correlating the background and foreground, and an improved SPIHT codec is also used in coding wavelet coefficients of foreground in lossless way and wavelet coefficients of background in loss way. Experimental results show the scheme in this paper is better than codec based on SPIHT directly, and the PSNR of the reconstructed image is also increased about 0.3-0.5dB in average under the same bit rate compared with that of the latter one.

FullText(HTML)

References(1)

References

J.L. Noga, Bayesian state-space modeling of Spatio-Temporal non-Gaussian radar return, [P. H.D. Dissertation], Signal Processing Lab, Department of Engineering, University of Cambridge,Dec. 1998.[2]C. Ridder.[J].et al., Adaptive background estimation and foreground detection using Kalmanfiltering, Proc. of International Conference on Recent Advance in Mechatronic, ICRAM95,Istanbul, Turkey.1995,:-[3]N. Friedman, S. Russell, Image segmentation in video sequences: A probabilistic approach, In Proc. of the Thirteen Conference on Uncertainty in Artificial Intelligence (UAI), Brown University, Providence, Rhode Island, USA. Aug. 1-3, 1997, 175-181.[4]J.M. Shapiro, Embedded image coding using zerotrees of wavelet coefficients, IEEE Trans. on Signal Processing, 1993, 41(12), 3445-3462.[5]A. Said, W. A. Pearman, A new fast and efficient image codec based on set partitioning in hierarchical tree, IEEE Trans. on Circuits and Syst. for Video Technol., 1996, 6(3), 243-250.[6]V.N. Ramaswamy, et al., Performance analysis of wavelets in embedded zerotree-based lossless image coding schemes, IEEE Trans. on Signal Processing, 1999, 47(3), 884-889.[7]Julien Reichel, Gloria Mengeaz, Marcus J. Nadenau, Integer wavelet transform for embedded lossy to lossless image compression, IEEE Trans. on Image Processing, 2001, 10(3), 383-392.[8]Xue Jianru.[J].Geng Xinli, Zheng Nanning, TWS tracking techniques based on adaptive Gaussian mixture model in phased array radar, Proc. of the 4th World Congress on Intelligent Control and Automation(WCICA02), Shanghai.2002,:-[9]G.K. Wallace, The JPEG Still Picture Compression Standard, Comm. ACM, 1991, 34(4), 30-44.[10]X. Wu, N. Memon, Context-based, adaptive, lossless image codec, IEEE Trans. on Comm., 1997,45(4), 437-444.

Relative Articles

Supplements(0)

Cited By

Proportional views