KSVD-Based Multiple Description Image Coding

Sun, Guina; Meng, Lili; Liu, Li; Tan, Yanyan; Zhang, Huaxiang

doi:10.1109/access.2018.2886823

Cited by 5 publications

(4 citation statements)

References 32 publications

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“…In each iteration the column that is most strongly correlated with the residue is chosen and the least square method is used to reduce the error involved. G. Sun et al proposed K-SVD based multiple description image coding (MDC) [25]. It partitioned the source into multiple bit streams and transmitted them through different channels respectively.…”

Section: Literature Surveymentioning

confidence: 99%

Dictionary Learning Based Adaptive Defect Detection In Complex Fabric Textures

2023

IJCDS

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Textile industry is one of the noticeable contributors to our nation's growth. The quality control procedures in textile production primarily involves the defect detection process. For detecting the defects in complex fabric textures, proper construction of sparse representation is needed. Existing fabric defect detection methods are incapable of detecting defects in more than one type of fabric and have increased detection time while missing few defects. In this paper, dictionary learning is proposed which is used to learn the sparse representation of complex data. Three types of greedy algorithms OMP, ROMP and STOMP are used for sparse representation and the results are compared based on computational speed and accuracy. The experimental results indicate that the STOMP algorithm gives accurate and precise results with lesser time consumption. STOMP achieves 99.3% reduction in time consumption compared to OMP and 97.7% reduction in time consumption compared to ROMP. Also, if ROMP and STOMP are used for signal recovery, the formulation of joint matrix is not essential resulting in reduced computational complexity.

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Section: Literature Surveymentioning

confidence: 99%

Dictionary Learning Based Adaptive Defect Detection In Complex Fabric Textures

2023

IJCDS

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“…Xu et al 24 compared the effect of Gaussian dictionaries and Chirp dictionaries on Lamb waves decomposition based on matching pursuit. The dictionary learning methods, such as optimal direction method, 25 K-singular value decomposition, 26 and online dictionary learning, 27,28 iterates and updates dictionaries according to the signal characteristics to optimize the dictionaries, which are computationally intensive but have a better decomposition effect to original signal. The UGW signal has sparsity in both time domain and frequency domain, which can be used to construct overcomplete dictionaries based on the characteristics of the UGW signal.…”

Section: Introductionmentioning

confidence: 99%

Cross-sparse representation based on dispersion dictionary for ultrasonic guided wave to messenger cable damage detection in cladding zone

Jian-xi

Lin

Hong

et al. 2023

Structural Health Monitoring

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The damage detection of messenger cable is an important guarantee to ensure the safety of electrified railways. The traditional nondestructive testing methods have difficulty in accurately detecting the damage of messenger cable in cladding zone. In this paper, a novel cross-sparse representation (CSR) method based on dispersion dictionary for ultrasonic guided wave (UGW) is proposed for the outer stranded wire of messenger cable in cladding zone. Firstly, the dispersion curves of UGW in multilayer spiral structure are solved by semi-analytical finite element method, to select an appropriate excitation signal. Secondly, the stationary phase approximation method is used to construct dispersion dictionary according to the dispersion curve which can characterize the modes and propagation distance of UGWs, and the CSR is proposed to separate and identify the damage signal. Thirdly, the simulation models of different damages in the outer stranded wire of messenger cable in the cladding zone are established to analyze the correlation between the damage rate and damage index in the cross-sections. Finally, the damage recognition effect based on CSR is analyzed and compared by experiments. The experimental results show that compared with the sparse representation (SR) method using traditional dictionary, the proposed method can improve the average accuracy of damage signal recognition from about 20% to 99.4% within a wide threshold range.

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“…The MDC coding splits the given data into multiple descriptions such that the received data quality can be dependent on the number of descriptions received. Some of the recent works using MDC techniques for image and video coding are as in [4] - [7]. In [4], MDC was used with the K-singular value decomposition (K-SVD) algorithm to achieve the sparse transform for reconstruction accuracy in image coding.…”

Section: Introductionmentioning

confidence: 99%

“…Some of the recent works using MDC techniques for image and video coding are as in [4] - [7]. In [4], MDC was used with the K-singular value decomposition (K-SVD) algorithm to achieve the sparse transform for reconstruction accuracy in image coding. The study in [5] proposed an MDC framework with auto-encoder to produce high-quality image reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Multiple Description Coding for Enhancing Outage and Video Performance Over Relay-Assisted Cognitive Radio Networks

et al. 2022

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Multimedia content delivery, such as video transmission over wireless networks, imposes significant challenges include spectrum capacity and packet losses. The cognitive radio (CR) technology is developed to solve the spectrum issue, while multiple description coding (MDC) is one of the promising source coding techniques to alleviate packet loss problems and exploit the benefit of path diversity. The source information was split into several descriptions in MDC, then transmitted over a network with multiple paths. The quality of the received data increases with the number of descriptions received at the receiver. In this paper, the proposed system comprises of relay-assisted cognitive radio network using the MDC technique for video transmission. In the simulations, the outage performance of the MDC scheme over two networks, which were relay-assisted network and non-relay network, were compared. Then, the outage probability was used to estimate the video quality, peak signal to noise ratio (PSNR) of the received video. The results obtained show the benefits of the relay assisted networks by 9% improvement on average outage performance over the non-relay network. Furthermore, the video performance improved by an average of 9% in PSNR compared to the non-relay system. INDEX TERMSCognitive radio, cognitive radio networks, H.264/AVC, multiple description coding (MDC), outage performance, interweave, peak signal to noise ratio (PSNR), relay.

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KSVD-Based Multiple Description Image Coding

Cited by 5 publications

References 32 publications

Dictionary Learning Based Adaptive Defect Detection In Complex Fabric Textures

Dictionary Learning Based Adaptive Defect Detection In Complex Fabric Textures

Cross-sparse representation based on dispersion dictionary for ultrasonic guided wave to messenger cable damage detection in cladding zone

Multiple Description Coding for Enhancing Outage and Video Performance Over Relay-Assisted Cognitive Radio Networks

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