Adaptive image transfer for wireless sensor networks (WSNs)

Nasri, Mohsen; Helali, Abdelhamid; Sghaier, Halim; Maâref, H.

doi:10.1109/dtis.2010.5487597

Cited by 25 publications

(18 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Step 1: At first, the input image is decomposed into number of subband coefficients with the help of wavelet transform DDDTCWT, then the coefficients are represented like Y=W+N (1) here, 'Y' represent the wavelet coefficient and 'W' is the input image coefficient and 'N' is the noise present in the image during image acquisition correspondingly.…”

Section: B Bivariate Shrink Methodsmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient Pass Parallel SPIHT based Image Compression using Double Density Dual Tree Complex Wavelet Transform for WSN

Samundiswary*¹,

Rekha²

2019

IJITEE

View full text Add to dashboard Cite

For the past two decades, wavelet based image compression algorithms for Wireless Sensor Network (WSN) has gained broad attention than that of the spatial based image compression algorithms. In that, Dual Tree Complex Wavelet Transforms (DTCWT) has provided better results in terms of image quality and high compression rate. However, the selection of DTCWT based image compressions for various WSN based applications is not practically suitable, due to the major limitations of WSN such as, low bandwidth, low energy consumption and storage space. Therefore, an attempt has been made in this paper to develop image compression through simulation by considering the modified block based pass parallel Set Partitioning In Hierarchical Trees (SPIHT) with Double Density Dual Tree Complex Wavelet Transform (DDDTCWT) for compressing the WSN based images. In addition, bivariate shrink method is also adopted with the DDDTCWT to obtain better image quality within less computation time. It is observed through simulation results that above mentioned proposed technique provides better performance than that of existing compression technique

show abstract

Section: B Bivariate Shrink Methodsmentioning

confidence: 99%

“…In recent years, image based way of communication is receiving a lot of attention in various applications of WSN domain [1]. However, the number of redundancies present inside the images engages huge storage space and in turn increases the energy consumption during WSN based communication.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Pass Parallel SPIHT based Image Compression using Double Density Dual Tree Complex Wavelet Transform for WSN

Samundiswary*¹,

Rekha²

2019

IJITEE

View full text Add to dashboard Cite

show abstract

“…Most of the work done in the field of image transmission has been for traditional power rich camera networks. For WSNs, Nasri et al [3], [7] propose adaptive image transfer using JPEG2000 and Discrete Wavelet Transforms. Through simulations show that their scheme optimizes network lifetime and reduces memory requirements.…”

Section: Related Workmentioning

confidence: 99%

PRoFIT—Priority-Based Routing Framework for Image Transmission in Visual Sensor Networks

Sheikh¹,

Naseer²,

Felemban³

2019

IJFCC

View full text Add to dashboard Cite

The primary goal of VSN deployment is to capture images and send them to power rich sink nodes. As image data is much larger than data sensed by a typical wireless sensor network (WSN), applications of VSN require much bigger amount of data to be transferred to the sink. Due to constraints of WSN such as low energy, limited CPU power and scarce memory, transmission of large amount of data becomes challenging. Furthermore, to take action, some VSN applications require critical image features sooner than the entire image. In this paper, Priority-based Routing Framework for Image Transmission (PRoFIT) is presented along with experimentation on real camera testbed. PRoFIT is designed to deliver critical image features at high priority to the sink node for early processing. PRoFIT does not reduce the total amount of data to be transmitted, however image features critical for some VSN applications are received at sink node much sooner using PRoFIT. Peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) analyses show that PRoFIT improves VSN application response time as compared to priority-less routing.Index Terms-Multimedia transmission, priority routing, visual sensor network, camera test-bed.

show abstract

“…The work in [ 34 ] proposes a distributed image compression scheme based on the JPEG2000 codec, exploiting the DWT technique and the Embedded Block Coding with Optimized Truncation (EBCOT) algorithm. As in [ 33 ], the authors argue that sensors nodes do not have sufficient computational power to compress a large volume of data, and in-network compression would be a reasonable solution to reduce energy consumption in source nodes and over the current path(s) toward the sink.…”

Section: Multimedia-based Cross-layer Optimization In Vsnsmentioning

confidence: 99%

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Costa

Guedes

2011

Sensors

View full text Add to dashboard Cite

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks.

show abstract

Adaptive image transfer for wireless sensor networks (WSNs)

Cited by 25 publications

References 10 publications

An Efficient Pass Parallel SPIHT based Image Compression using Double Density Dual Tree Complex Wavelet Transform for WSN

An Efficient Pass Parallel SPIHT based Image Compression using Double Density Dual Tree Complex Wavelet Transform for WSN

PRoFIT—Priority-Based Routing Framework for Image Transmission in Visual Sensor Networks

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Contact Info

Product

Resources

About