Multiple description wavelet-based image coding using correlating transforms

Khelil, Khaled; Bekka, Raı ̈s El Hadi; Djebari, Ali; Rouvaen, J.M.

doi:10.1016/j.aeue.2006.07.003

Cited by 17 publications

(6 citation statements)

References 10 publications

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“…In another approach pioneered by MD coder is constructed using a linear transform, which introduces a controlled amount of correlation between the vectors that have been separately describing. We propose MD scheme based on NSCT where we utilise MDTC technique used by and Khelil et al (2007) and adapt the OMP algorithm developed for sparse representation of images (Rebollo and Bowley, 2013) to minimise coefficients number of NSCT. The next scheme focus on the case of four channels, in such coder a sequence of source vectors is given to construct descriptions of similar importance, which are transmitted over separate channels to the decoder, where the latest has to reconstruct the original signal in the case of loss of one or more sequence.…”

Section: Mdtc Using Pairwise Correlating Transformmentioning

confidence: 99%

“…Other designs of MDC scheme based on wavelet transform considering the use of pairwise correlating transform PCT, have been addressed by and Wang et al (2001). Recently, a wavelet transform-based MDTC approach for image coding is proposed by Khelil et al (2007Khelil et al ( , 2011 which is an improvement of MDTC studied by Kovacevic (1998, 2001), and Orchard et al (1997) in the case of four descriptions generated from the wavelet decomposition step where they constitute significant MDTC coder based on wavelet transformation and uniform quantisation with constant step for each description issue from the subbands obtained after applying one level decomposition. Ashwani et al (2014) investigated the MDTC-DWT scheme for transmission over OFDM fading broadcast channels, where they applied a cascade structure for generating four descriptions and a pairwise correlating transform to add a controlled amount of correlation.…”

Section: Introductionmentioning

confidence: 99%

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Image compression-based multiple description transform coding using NSCT and OMP approximation

Naimi

Belloulata

2018

IJCVR

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In this paper, we present a novel multiple description transform image coding architecture, which uses an attractive transform called non-subsampled contourlet transform (NSCT). It combines NSCT and orthogonal matching pursuit algorithm (OMP) to give a sparse representation of images, aiming at solving the compression problem due to the redundancy property of NSCT. In this way, OMP turns to give a solution to remove the redundancies. We evaluate the performance of our image coder in the case of four descriptions that are dispatched over different channels. The experimentations show that the proposed method is efficient and the potential using NSCT than DWT in multiple description image coding, is evaluated by PSNR in each case of packet loss, where every description can reconstruct the image with acceptable fidelity, the later is much better if all descriptions are available.

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Section: Mdtc Using Pairwise Correlating Transformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Image compression-based multiple description transform coding using NSCT and OMP approximation

Naimi

Belloulata

2018

IJCVR

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“…The first step is to design the scaling filter knowledgeably, and the second is to select the wavelet filters from the given scaling filter. Khelila et al (2007),propose a new and simple multiple description transform coder (MDC) scheme based on the employing the discrete wavelet transform (DWT) instead of the DCT. Dubeau et al (2004), present a non-uniform "Haar" wavelet and its multi-resolution analysis on a bounded interval which includes transforms, compression, and reconstruction at a single value.…”

Section: Wavelet Transformmentioning

confidence: 99%

A review of wave-net identical learning & filling-in in a decomposition space of (JPG-JPEG) sampled images

et al. 2010

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Continuous flow to send images via encrypted wireless channels may reduce the efficiency of transmission. This is due to the damage or loss of the numerous macro-blocks from these images. Therefore, it is difficult to rebuild these patches from the point of reception. Many algorithms have been proposed in the past decade, particularly error concealment (EC) algorithms. In this paper, we focus on the algorithms that have high efficiency to fill-in the corrupted patches. On the other hand, we also present a new way of detecting the horizontal and vertical gradients especially, in the un-smooth patches. This improves the edge detector filter. Ultimately, a novel scheme for vertical and horizontal interpolation between the corrupted pixels and the non-corrupted adjacent pixels is achieved by improving the efficiency of filling-in. We used a new technique known as the wave-net model. This model combines the wavelet with the neural network classifier (NNC). The neural network was trained in advance to reduce the error extent for the pixels that may occur in the error. The experimental results were convincing and close to the desired. The proposed method is able to enhance image quality in term of both visual perception and the blurriness effects (BE).

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“…When one is lost, it can be estimated from another received by the correlation between two groups. And many related improvements for MDC based on wavelet transform are developed [9]- [11]. In [12], a new technique that produces multiple description by quincunx spatial multiplexing is studied.…”

Section: Introductionmentioning

confidence: 99%

KSVD-Based Multiple Description Image Coding

et al. 2019

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In this paper, we present a new multiple description coding scheme, which is based on a sparse dictionary training method called K singular value decomposition (KSVD). In the proposed scheme, each description encodes one source subset with a small quantization stepsize, and other subsets are predictively coded with a large quantization stepsize. The source processed by the KSVD becomes sparse, which can improve the coding efficiency. The proposed scheme is then applied to lapped transform-based multiple description image coding. Finally, image coding results show that the proposed scheme achieves a better performance than the current state-of-the-art multiple description coding methods. INDEX TERMS K singular value decomposition (KSVD), multiple description coding, sparse representation.

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Multiple description wavelet-based image coding using correlating transforms

Cited by 17 publications

References 10 publications

Image compression-based multiple description transform coding using NSCT and OMP approximation

Image compression-based multiple description transform coding using NSCT and OMP approximation

A review of wave-net identical learning & filling-in in a decomposition space of (JPG-JPEG) sampled images

KSVD-Based Multiple Description Image Coding

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