In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is a...In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is applied on each video frame independently to extract the low frequency components for each frame and then the low frequency parts of all frames are coded using H.264/AVC codec. On the other hand, the high frequency parts of the video frames are coded by Run Length Coding algorithm, after applying a threshold to neglect the low value coefficients. Experiments show that our proposed method can achieve better rate-distortion performance at very low bit-rate applications below 16 kbits/s compared to applying H.264/AVC standard directly to all frames. Applications of our proposed video coding technique include video telephony, video-conferencing, transmitting or receiving video over half-rate traffic channels of GSM networks.展开更多
In this paper, at large class of two-dimensional orthogonal wavelet filters, (lowpass and highpass), are presented in explicit expression. We also characterize the filters with linear phase in this case. Some examples...In this paper, at large class of two-dimensional orthogonal wavelet filters, (lowpass and highpass), are presented in explicit expression. We also characterize the filters with linear phase in this case. Some examples are also given, including non-separable filters with linear phase.展开更多
Among existing remote sensing applications, land-based X-band radar is an effective technique to monitor the wave fields, and spatial wave information could be obtained from the radar images. Two-dimensional Fourier T...Among existing remote sensing applications, land-based X-band radar is an effective technique to monitor the wave fields, and spatial wave information could be obtained from the radar images. Two-dimensional Fourier Transform （2-D FT） is the common algorithm to derive the spectra of radar images. However, the wave field in the nearshore area is highly non-homogeneous due to wave refraction, shoaling, and other coastal mechanisms. When applied in nearshore radar images, 2-D FT would lead to ambiguity of wave characteristics in wave number domain. In this article, we introduce two-dimensional Wavelet Transform （2-D WT） to capture the non-homogeneity of wave fields from nearshore radar images. The results show that wave number spectra by 2-D WT at six parallel space locations in the given image clearly present the shoaling of nearshore waves. Wave number of the peak wave energy is increasing along the inshore direction, and dominant direction of the spectra changes from South South West （SSW） to West South West （WSW）. To verify the results of 2-D WT, wave shoaling in radar images is calculated based on dispersion relation. The theoretical calculation results agree with the results of 2-D WT on the whole. The encouraging performance of 2-D WT indicates its strong capability of revealing the non-homogeneity of wave fields in nearshore X-band radar images.展开更多
文摘In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is applied on each video frame independently to extract the low frequency components for each frame and then the low frequency parts of all frames are coded using H.264/AVC codec. On the other hand, the high frequency parts of the video frames are coded by Run Length Coding algorithm, after applying a threshold to neglect the low value coefficients. Experiments show that our proposed method can achieve better rate-distortion performance at very low bit-rate applications below 16 kbits/s compared to applying H.264/AVC standard directly to all frames. Applications of our proposed video coding technique include video telephony, video-conferencing, transmitting or receiving video over half-rate traffic channels of GSM networks.
文摘In this paper, at large class of two-dimensional orthogonal wavelet filters, (lowpass and highpass), are presented in explicit expression. We also characterize the filters with linear phase in this case. Some examples are also given, including non-separable filters with linear phase.
基金Project supported by the Open Research Fund of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University (Grant No. 2008491011)the Special Fund of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University (Grant Nos. 2009585812, 2009586712)+1 种基金the Key Project of Chinese Ministry of Education (Grant No. 20100094120008)supported by the Funds for the Central Universities, Hohai University (Grant No. 2009B00214)
文摘Among existing remote sensing applications, land-based X-band radar is an effective technique to monitor the wave fields, and spatial wave information could be obtained from the radar images. Two-dimensional Fourier Transform （2-D FT） is the common algorithm to derive the spectra of radar images. However, the wave field in the nearshore area is highly non-homogeneous due to wave refraction, shoaling, and other coastal mechanisms. When applied in nearshore radar images, 2-D FT would lead to ambiguity of wave characteristics in wave number domain. In this article, we introduce two-dimensional Wavelet Transform （2-D WT） to capture the non-homogeneity of wave fields from nearshore radar images. The results show that wave number spectra by 2-D WT at six parallel space locations in the given image clearly present the shoaling of nearshore waves. Wave number of the peak wave energy is increasing along the inshore direction, and dominant direction of the spectra changes from South South West （SSW） to West South West （WSW）. To verify the results of 2-D WT, wave shoaling in radar images is calculated based on dispersion relation. The theoretical calculation results agree with the results of 2-D WT on the whole. The encouraging performance of 2-D WT indicates its strong capability of revealing the non-homogeneity of wave fields in nearshore X-band radar images.
