1. What are the contributions mentioned in the paper "A fast decoder for compressed sensing based multiple description image coding" ?
This paper proposes an MDC decoder for Compressed Sensing ( CS ) based MDC.
read more
A fast decoder for Compressed Sensing based multiple description image coding
Mashud Hyder,Kaushik Mahata +1 more
- 07 Nov 2009
- pp 2101-2104
TL;DR: This paper proposes an MDC decoder for Compressed Sensing (CS) based MDC that minimizes ℓ0 norm of the total variation of the image in a recursive manner, making it effective when different descriptions experience different time delays in the network.
read more
Abstract: Multiple description coding (MDC) offers an elegant approach to data transmission over lossy packet-based networks. This paper proposes an MDC decoder for Compressed Sensing (CS) based MDC. Our decoder minimizes l0 norm of the total variation of the image in a recursive manner, making it effective when different descriptions experience different time delays in the network. The proposed approach brings in a significant performance improvement in reconstruction accuracy and reconstruction time.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Most frequently asked questions
Figures
Table 1. RecLZA Algorithm 
Fig. 3. Two descriptions are added at a time. 
Fig. 2. Number of iterations and computation time required to reconstruct image when one description is added at a time. 
Fig. 1. PSNR versus number of descriptions for “Camera Man” image (256× 256). One description is added at a time.
Citations
A New Polyphase Down-Sampling-Based Multiple Description Image Coding
TL;DR: The experimental results indicate that the proposed NPDS-MDC scheme offers clearly superior performance, especially at high bit rates, as compared to the state-of-the-art methods for various types of images.
5
IoT-Based Compressive Sensing for Real-World Infrastructural Monitoring Application
Matteo Zerbino,Igor Bisio,Chiara Garibotto,Fabio Lavagetto,Andrea Sciarrone +4 more
- 28 May 2023
TL;DR: Numerical results show that the CS approach to inertial signals sensed by innovative IoT devices is able to efficiently estimate the infrastructures modal frequencies with an innovative inertial IoT prototype by achieving a compression level around 20 times below the Nyquist rate.
1
References
Nonlinear total variation based noise removal algorithms
TL;DR: In this article, a constrained optimization type of numerical algorithm for removing noise from images is presented, where the total variation of the image is minimized subject to constraints involving the statistics of the noise.
17.3K
Atomic Decomposition by Basis Pursuit
TL;DR: Basis Pursuit (BP) is a principle for decomposing a signal into an "optimal" superposition of dictionary elements, where optimal means having the smallest l1 norm of coefficients among all such decompositions.
11.3K
Atomic Decomposition by Basis Pursuit
TL;DR: This work gives examples exhibiting several advantages over MOF, MP, and BOB, including better sparsity and superresolution, and obtains reasonable success with a primal-dual logarithmic barrier method and conjugate-gradient solver.
Solution of Sparse Indefinite Systems of Linear Equations
TL;DR: The method of conjugate gradients for solving systems of linear equations with a symmetric positive definite matrix A is given as a logical development of the Lanczos algorithm for tridiagonalizing...
1.8K
Multiple description coding: compression meets the network
TL;DR: By allowing image reconstruction to continue even after a packet is lost, this type of representation can prevent a Web browser from becoming dormant, and the source can be approximated from any subset of the chunks.
Related Papers (5)
Ottavio Campana,Roberto Contiero +1 more
- 01 Oct 2006
Manuela Pereira,Marc Antonini,Michel Barlaud +2 more
- 07 Nov 2002
Yantian Hou,Feng Liu +1 more
- 28 Oct 2011