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Layered multiple description video coding using dual-tree discrete wavelet transform and H.264/AVC

MULTIMEDIA TOOLS AND APPLICATIONS 2016年第5期75卷 2801-2814页

作者： Chen, Jing Cai, Canhui Li, Li Li, Cuihua Xiamen Univ Sch Informat Sci & Engn Xiamen Peoples R China Huaqiao Univ Sch Informat Sci & Engn Xiamen Peoples R China

A novel hybrid layered multiple description video coding (HLMDVC) algorithm is proposed to provide a robust and flexible video transmission via unreliable networks, like Internet or the wireless network. First, the input video sequence is encoded by a standard H.264/AVC encoder in low bit rate to form the base layer, which is then duplicated to each description. Second, the 3D dual-tree discrete wavelet transform is performed on the difference between the reconstructed base layer and the input sequence to produce four wavelet coefficient trees. Then the noise shaping is used to reduce the redundancy of these coefficient trees. After that, the four sparse wavelet coefficient trees are separately encoded by 3D-SPIHT encoders. The resulted four bitstreams are partitioned into two groups, separately forming enhancement layers of two descriptions. The redundancy of the proposed multiple description video coding scheme can be easily adjusted by changing the bitrate of the base layer to fit for different transmission channels. The directional selectivity feature of 3D dual-tree discrete wavelet transform frees the enhancement layer coding from the time consuming motion estimation, such that no mismatch happens and the coding efficiency is improved. Simulation results have shown that the quality of the reconstructed video of the proposed HLMDVC algorithm is superior to that by the state-of-the-art multiple description video coding methods.

关键词： Multiple description coding Video coding Layered coding dual-tree discrete wavelet transform H.264/AVC

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HEVC and 3D dual-tree discrete wavelet transform based multiple description video coding

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2016年第4期16卷 955-965页

作者： Chen, Jing Liao, Jie Yang, Yuhang Cai, Canhui Huaqiao Univ Sch Informat Sci & Engineer Xiamen 361021 Fujian Peoples R China Xiamen Key Lab Mobile Multimedia Commun Xiamen 361021 Fujian Peoples R China

To improve the robustness of video transmission, a layered HEVC multiple description video coding (MDVC) based on 3D dual-tree discrete wavelet transform (3D DDWT) is proposed in this paper. The base layer of the coding structure consists of bitstreams coded by an HEVC with low bitrate, and then duplicated to each description. The error frames of the reconstructed base layer and the input video sequence are coded by a 3D discrete wavelet transform encoder to produce four coefficient trees with redundancy. After noise-shaping, these four trees are partitioned into two groups, forming the enhancement layer of diverse descriptions. As the directional selection property of 3D DDWT, the error matching problem can be solved without performing the motion estimation and motion compensation in each description, the complexity of the MDVC algorithm can also be reduced. Experimental results have shown that the proposed algorithm improves the error resiliency of HEVC while maintaining the coding efficiency.

关键词： HEVC multiple description video coding dual-tree discrete wavelet transform

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3D dual-tree discrete wavelet transform Based Multiple Description Video Coding 11

3D Dual-Tree Discrete Wavelet Transform Based Multiple Descr...

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11th International Conference on Signal Processing and Multimedia Applications (SIGMAP) is part of 11th International Joint Conference on E-Business and Telecommunications (ICETE)

作者： Chen, Jing Cai, Canhui Li, Li Huaqiao Univ Sch Informat Sci & Engn Xiamen Peoples R China Xiamen Univ Sch Informat Sci & Engn Xiamen Peoples R China

ISBN: (纸本)9789898565969

A 3D dual-tree discrete wavelet transform (DT-DWT) based multiple description video coding algorithm is proposed to combat the transmitting error or packet loss due to Internet or wireless network channel failure. Each description of the proposed multiple description coding scheme consists of a base layer and an enhancement layer. First, the input image sequence is encoded by a standard H.264 encoder in low bit rate to form the base layer, which is then duplicated to each description. Second, the difference between the reconstructed base layer and the input image sequence is encoded by a 3D dual-tree wavelet encoder to produce four coefficient trees. After noise-shaping, these four trees are partitioned into two groups, individually forming enhancement layers of two descriptions. Since the 3D DT-DWT equips 28 directional subbands, the enhancement layer can be coded without motion estimation. The plenty of directional selectivity of DT-DWT solves the mismatch problem and improves the coding efficiency. If all descriptions are available in the receiver, a high quality video can be reconstructed by a central decoder. If only one description is received, a side decoder can be used to reconstruct the source with acceptable quality. Simulation results have shown that the quality of reconstructed video by the proposed algorithm is superior to that by the state-of-the-art multiple description video coding methods.

关键词： Multiple Description Coding Video Coding dual-tree discrete wavelet transform Layer Coding

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UAV Image Denoising Using Adaptive dual-tree discrete wavelet Packets Based on Estimate the Distributing of the Noise

UAV Image Denoising Using Adaptive Dual-Tree Discrete Wavele...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Fang, Liu Yang, Biao Beijing Univ Technol Sch Elect Informat & Control Engn Beijing 100124 Peoples R China North China Univ Technol Dept Automat Beijing 100041 Peoples R China

ISBN: (纸本)9781467313988

Unmanned Aerial Vehicles (UAV) digital images are often badly degraded by noise during dynamic acquisition and transmission process. Denoising is very important and difficult for UAV-vision Guided, because natural scene image is complicated and having lots of the edges and texture details. The image denoising algorithm based on adaptive dual-tree discrete wavelet packets(ADDWP) which combine the dual-tree discrete wavelet transform(DDWT) and the wavelet packets is proposed in this paper. In ADDWP, DDWT subbands are further decomposed into wavelet packets with anisotropic decomposition, so that the resulting wavelets have elongated support regions and more orientations than DDWT wavelets. To determine the decompoisition structure, we using the signal-to-noise ratio to estimate the distributing of the denoising in order to search the more denoising subbands to decomposition it again. So we can get adaptive decompoisition structure of wavelet packets. The new algorithm has significantly lower computational complexity than a previously developed optimal basis selection algorithm. For denoising the ADDWP coefficients, a statistical model is used to exploit the relation of the coefficients in order to distinguish the noise and the signal. The proposed denoising scheme gives better performance than several state-of-the-art DDWT-based schemes for images with rich directional features. The visual quality of images denoised by the proposed scheme is also superior.

关键词： UAV-vision Guided dual-tree discrete wavelet transform wavelet packets signal-to-noise ratio image denoising

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A new wavelet-based fuzzy single and multi-channel image denoising

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IMAGE AND VISION COMPUTING 2010年第12期28卷 1611-1623页

作者： Saeedi, Jamal Moradi, Mohammad Hassan Faez, Karim Amirkabir Univ Technol Dept Elect Engn Tehran Iran Amirkabir Univ Technol Dept Bioelect Biomed Engn Tehran Iran

In this paper, we propose a new wavelet shrinkage algorithm based on fuzzy logic. In particular, intra-scale dependency within wavelet coefficients is modeled using a fuzzy feature. This feature space distinguishes between important coefficients, which belong to image discontinuity and noisy coefficients. We use this fuzzy feature for enhancing wavelet coefficients' information in the shrinkage step. Then a fuzzy membership function shrinks wavelet coefficients based on the fuzzy feature. In addition, we extend our noise reduction algorithm for multi-channel images. We use inter-relation between different channels as a fuzzy feature for improving the denoising performance compared to denoising each channel, separately. We examine our image denoising algorithm in the dual-tree discrete wavelet transform, which is the new shiftable and modified version of discrete wavelet transform. Extensive comparisons with the state-of-the-art image denoising algorithm indicate that our image denoising algorithm has a better performance in noise suppression and edge preservation. (c) 2010 Elsevier B.V. All rights reserved.

关键词： Image denoising dual-tree discrete wavelet transform Fuzzy membership function Multi-channel image

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Simultaneous denoising and compression of multispectral images

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JOURNAL OF APPLIED REMOTE SENSING 2013年第1期7卷

作者： Hagag, Ahmed Amin, Mohamed Abd El-Samie, Fathi E. Egyptian E Learning Univ Dept Informat Technol Fac Informat Technol Giza 12611 Egypt Menoufia Univ Dept Math Fac Sci Shibin Al Kawm 32511 Egypt Menoufia Univ Dept Elect & Elect Commun Fac Elect Engn Menoufia 32952 Egypt

A new technique for denoising and compression of multispectral satellite images to remove the effect of noise on the compression process is presented. One type of multispectral images has been considered: Landsat Enhanced Thematic Mapper Plus. The discrete wavelet transform (DWT), the dual-tree DWT, and a simple Huffman coder are used in the compression process. Simulation results show that the proposed technique is more effective than other traditional compression-only techniques. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： multispectral compression denoising discrete wavelet transform dual-tree discrete wavelet transform

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Infrared and visible image fusion using fuzzy logic and population-based optimization

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APPLIED SOFT COMPUTING 2012年第3期12卷 1041-1054页

作者： Saeedi, Jamal Faez, Karim Amirkabir Univ Technol Dept Elect Engn Tehran Polytech Tehran Iran

This paper presents a new wavelet-based algorithm for the fusion of spatially registered infrared and visible images. wavelet-based image fusion is the most common fusion method, which fuses the information from the source images in the wavelet transform domain according to some fusion rules. We specifically propose new fusion rules for fusion of low and high frequency wavelet coefficients of the source images in the second step of the wavelet-based image fusion algorithm. First, the source images are decomposed using dual-tree discrete wavelet transform (DT-DWT). Then, a fuzzy-based approach is used to fuse high frequency wavelet coefficients of the IR and visible images. Particularly, fuzzy logic is used to integrate the outputs of three different fusion rules (weighted averaging, selection using pixel-based decision map (PDM), and selection using region-based decision map (RDM)), based on a dissimilarity measure of the source images. The objective is to utilize the advantages of previous pixel-and region-based methods in a single scheme. The PDM is obtained based on local activity measurement in the DT-DWT domain of the source images. A new segmentation-based algorithm is also proposed to generate the RDM using the PDM. In addition, a new optimization-based approach using population-based optimization is proposed for the low frequency fusion rule instead of simple averaging. After fusing low and high frequency wavelet coefficients of the source images, the final fused image is obtained using the inverse DT-DWT. This new method provides improved subjective and objectives results as compared to previous image fusion methods. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Infrared and visible images dual-tree discrete wavelet transform Fuzzy logic Population-based optimization

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A classification and fuzzy-based approach for digital multi-focus image fusion

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PATTERN ANALYSIS AND APPLICATIONS 2013年第3期16卷 365-379页

作者： Saeedi, Jamal Faez, Karim Amirkabir Univ Technol Dept Elect Engn Tehran Polytech Tehran Iran

This paper presents a new wavelet-based method for fusion of spatially registered multi-focus images. We have formulated the image fusion process as a two-class classification problem: in and out-of-focus classes. First, a 12-dimensional feature vector using dual-tree discrete wavelet transform (DT-DWT) sub-bands of the source images are extracted, and then a trained two-class fisher classifier projects it to the class labels. The classifier output is used as a decision map for fusing high-frequency wavelet coefficients of multi-focus source images in different directions and decomposition levels of the DT-DWT. In addition, there is an uncertainty for selecting high-frequency wavelet coefficients in smooth regions of source images, which causes some misclassified pixels in the classification output or the decision map. In order to solve this uncertainty and integrate as much information as possible from the source images into the fused image, we propose an algorithm based on fuzzy logic, which combines outputs of two different fusion rules based on a dissimilarity measure from the source images: Selection based on the decision map and weighted averaging. An estimation of the decision map is also used for fusing low-frequency wavelet coefficients of the source images instead of simple averaging. After fusing low- and high-frequency wavelet coefficients of the source images, the final fused image is obtained using the inverse DT-DWT. This new method provides improved subjective and objectives results (more than 4.5 dB on average) as compared to previous fusion methods.

关键词： Multi-focus image fusion dual-tree discrete wavelet transform Fisher classifier Fuzzy logic

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The New Segmentation and Fuzzy Logic based Multi-Sensor Image Fusion

The New Segmentation and Fuzzy Logic based Multi-Sensor Imag...

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24th International Conference Image and Vision Computing New Zealand

作者： Saeedi, Jamal Faez, Karim Amirkabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781424446971

In this paper, we propose a new multi-resolution fusion algorithm for spatially registered multi-sensor images fusion. First, we use a modified watershed algorithm to produce a region map of source images. This segmentation is then used to generate region-based decision map, which is obtained based on local texture features in the dual-tree discrete wavelet transform domain. The region-based decision map is very accurate for selecting high frequency coefficients between the source images compare to the pixel-based decision map, but very important details of source images is missed in the final fused image. In this study, we propose an algorithm based on fuzzy logic, which uses both pixel and region-based decision map based on a dissimilarity measure of source images for fusion rule. Also a region-based activity measure of each source image is used for low frequency fusion rule instead of simple averaging. Our new method provides improved subjective and objectives results compared to the previously pixel and region-based fusion methods.

关键词： image fusion dual-tree discrete wavelet transform watershed segmentation multi-sensor images

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Analysis of ECG Signal Denoising Using discrete wavelet transform 2

Analysis of ECG Signal Denoising Using Discrete Wavelet Tran...

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2nd IEEE International Conference on Engineering and Technology (ICETECH)

作者： Shemi, P. M. Shareena, E. M. MES Coll Marampally Dept Elect Ernakulam Kerala India

ISBN: (纸本)9781467399166

Denoising is considered as one of the important tasks in signal processing. ECG signal analysis is very important for detecting heart diseases. The amplitude and frequency of ECG signals may vary due to corruption of noises and that may further cause problems to detect the actual abnormality. In this paper performance comparison of denoising of ECG signals based on different wavelet transform techniques is implemented. discrete wavelet transform (DWT) and its expansive forms such as double-density discrete wavelet transform (DDDWT), dual-tree discrete wavelet transform (DTDWT) and double-density dual-tree discrete wavelet transform (DDDTDWT) techniques employing thresholding algorithm are presented for signal denoising. The ECG signals taken from MIT-BIH arrhythmia database are corrupted with different types of noise and used for the analysis. The results of MATLAB simulations show that the algorithm based on double-density dual-tree discrete wavelet transform is more effective and gives better performance in terms of both SNR and RMSE.

关键词： ECG denoising Double-density discrete wavelet transform dual-tree discrete wavelet transform Double-Density dual-tree discrete wavelet transform

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