P.L. Dragotti, S.D. Servetto and M. Vetterli, "Analysis of Optimal Filter Banks for Multiple Description Coding," in Proc. IEEE Data Compression Conf., Snowbird, Utah, March 2000, pp. 323-332. Home/Search Document Details and Download
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Quantized Oversampled Filter Banks with Erasures - Dragotti, Kovacevic, Goyal (2000) Self-citation (Dragotti) (Correct)
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P.L. Dragotti, S.D. Servetto and M. Vetterli, "Analysis of Optimal Filter Banks for Multiple Description Coding," in Proc. IEEE Data Compression Conf., Snowbird, Utah, March 2000, pp. 323-332.
Wavelet Footprints and Frames for Signal Processing and.. - Dragotti (2002) Self-citation (Dragotti) (Correct)
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P.L. Dragotti, S. Servetto, and M. Vetterli. Analysis of optimal filter banks for multiple description coding. In Data Compression Conference, Snowbird, Utah (USA), March 2000.
Wavelet Footprints and Frames for Signal Processing and.. - Dragotti (2002) Self-citation (Dragotti) (Correct)
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P.L. Dragotti, S. Servetto, and M. Vetterli. Analysis of optimal filter banks for multiple description coding. In Data Compression Conference, Snowbird, Utah (USA), March 2000.
Quantized Oversampled Filter Banks with Erasures - Dragotti, Kovacevic, Goyal (2001) Self-citation (Dragotti) (Correct)
.... Gamma N erasures. The reconstruction process is linear. We wish to find filter bank properties that minimize the mean square error (MSE) between the input and the reconstructed sequences. To analyze cases with more than M Gamma N erasures requires a statistical model for the input sequence. In [5, 9, 12], the input sequence is a stationary Gaussian source; in [5, 12] the case M = N = 2 and one erasure is considered, while in [9] the case M = 3 and N = 2 and up to two erasures is analyzed. In this work we do not make any assumptions on the input source. However, we use a statistical model for the ....
....to find filter bank properties that minimize the mean square error (MSE) between the input and the reconstructed sequences. To analyze cases with more than M Gamma N erasures requires a statistical model for the input sequence. In [5, 9, 12] the input sequence is a stationary Gaussian source; in [5, 12] the case M = N = 2 and one erasure is considered, while in [9] the case M = 3 and N = 2 and up to two erasures is analyzed. In this work we do not make any assumptions on the input source. However, we use a statistical model for the quantization error; the reconstruction then depends only on the ....
P.L. Dragotti, S.D. Servetto and M. Vetterli, "Analysis of Optimal Filter Banks for Multiple Description Coding," in Proc. IEEE Data Compression Conf., Snowbird, Utah, March 2000, pp. 323-332.
Filter Bank Frame Expansions with Erasures - Kovacevic, Dragotti, Goyal (2002) (1 citation) Self-citation (Dragotti) (Correct)
....N erasures. The reconstruction process is linear. We wish to find properties of the filter banks that minimize the mean square error (MSE) between the input and the reconstructed sequences. To analyze cases with more than M Gamma N erasures requires a statistical model for the input sequence. In [12], 24] 33] 1 A common alternative spelling of Naimark is Neumark. KOVA CEVI C, DRAGOTTI AND GOYAL: FILTER BANK FRAME EXPANSIONS WITH ERASURES 2 h 1 h M g 1 g M Q 1 Q M N N N x x analysis filter bank synthesis filter bank N y 1 y M y 1 y M Fig. 1. Abstraction of a lossy network ....
....the number of erasures during the transmission. We assume there are no more than M Gamma N erasures. The reconstruction process is performed by the synthesis filter bank. The choice of synthesis filters depends on which channels are received. the input sequence is a stationary Gaussian source; in [12], 33] the case M = N = 2 and one erasure is considered, while in [24] the case M = 3 and N = 2 and up to two erasures is analyzed. In this work we do not make any assumptions on the input source. Rather, a statistical model for the quantization error makes the reconstruction quality depend only ....
P.L. Dragotti, S.D. Servetto, and M. Vetterli. Analysis of optimal filter banks for multiple description coding. In Proc. Data Compr. Conf., pages 323--332, Snowbird, Utah, March 2000.
Multiple Description Coding: Compression Meets the Network - Goyal (2001) (38 citations) (Correct)
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P.L. Dragotti, S.D. Servetto, and M. Vetterli, "Analysis of optimal filter banks for multiple description coding," in Proc. IEEE Data Compression Conf., Snowbird, UT, Mar. 2000, pp. 323-332.
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