Efficient JPEG 2000 Image Compression Scheme for Multihop Wireless Networks

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

doi:10.12928/telkomnika.v9i2.702

Cited by 15 publications

(7 citation statements)

References 10 publications

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“…They are utilized in case of risk to send alert signs to explicit area, and are ordinarily sorted as coercion caution frameworks. The sorts of coercion caution frameworks are: Identification alert: In this framework, a straightforward compact gadget is utilized to recognize the get to capable work force (proprietor) of the gadget, Panic catch alert [15][16]. A push catch mounted in a settled area, and an area caution: a versatile gadget that finds and tracks the individual who actuated caution [17].…”

Section: Related Workmentioning

confidence: 99%

An adaptive intelligent alarm system for wireless sensor network

Salman

Khalaf

Abdulsaheb

2019

IJEECS

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Security is one of the imperative issues in an advanced local condition. The current center around formative and research issues of Wireless Sensor Network(WSN) based Smart Home. WSN based shrewd home detection system gives a safe and safe living condition. A Wireless Sensor System (WSN) is a system which is building by utilizing little independent hubs (sensors). Its motivation is to screen certain ecological parameters, for example, temperature, dampness, brilliance, weight, sound, movement, and so forth. This paper depicts the improvement of a smart home condition dependent on exact Wireless Sensor Network and furthermore depicts private vitality observing and controlling procedures for keen home systems administration framework. This paper proposes a basic and adaptable remote arrange for domestics computerization of temperature, moistness, gas, movement and light by executing dependable sensor hubs which can be controlled too observed. This innovation offers energizing and new chance to build the availability of devices inside the home for the home computing.

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Section: Related Workmentioning

confidence: 99%

An adaptive intelligent alarm system for wireless sensor network

Salman

Khalaf

Abdulsaheb

2019

IJEECS

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“…Nasri et al [24] proposed an effective JPEG2000 image compression method for multihop WSNs. This proposed method distributes the image compression tasks among SNs along the way to the BS, similar to the abovementioned studies.…”

Section: Related Workmentioning

confidence: 99%

Distributed Image Compression Architecture over Wireless Multimedia Sensor Networks

Heng

So-In

Nguyen

2017

Wireless Communications and Mobile Computing

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In a wireless multimedia sensor network (WMSN), the minimization of network energy consumption is a crucial task not just for scalar data but also for multimedia. In this network, a camera node (CN) captures images and transmits them to a base station (BS). Several sensor nodes (SNs) are also placed throughout the network to facilitate the proper functioning of the network. Transmitting an image requires a large amount of energy due to the image size and distance; however, SNs are resource constrained. Image compression is used to scale down image size; however, it is accompanied by a computational complexity trade-off. Moreover, direct image transmission to a BS requires more energy. Thus, in this paper, we present a distributed image compression architecture over WMSN for prolonging the overall network lifetime (at high throughput). Our scheme consists of three subtasks: determining the optimal camera radius for prolonging the CN lifetime, distributing image compression tasks among the potential SNs to balance the energy, and, finally, adopting a multihop hierarchical routing scheme to reduce the long-distance transmission energy. Simulation results show that our scheme can prolong the overall network lifetime and achieve high throughput, in comparison with a traditional routing scheme and its state-of-the-art variants.

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“…In recent years lot of research has been done to enhance the quality of received image after transmission in noisy channel, this problem can be solved using different techniques (source coding, channel coding , joint source channel coding or by optimize in restoration filters) as shown in articles [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Data analysis for image transmitted using Discrete Wavelet Transform and Vector Quantization compression

Khelifi¹,

Lakhdar²,

Elawady³

2016

TELKOMNIKA

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In this paper we are going to study the effect of channel noise in image compressed with vector quantization and discrete wavelet transform. IntroductionIn recent years lot of research has been done to enhance the quality of received image after transmission in noisy channel, this problem can be solved using different techniques (source coding, channel coding , joint source channel coding or by optimize in restoration filters) as shown in articles [1][2][3].A good representation and compression of image can make the difference on the quality of received image, also to understand how the channel noise attack the transmitted data can be provide an efficient techniques with less consumption in resource (processing unit, time, data size, …) and bandwidth usage.In image compression, we know that, the combination between vector quantization and discrete wavelet transform provide a good representation of reconstructed image. Since the discrete wavelet transform analyze image and give us lot of data about 2D signal which make the difference in the quality of reconstructed image however In case of transmission the compression using VQ and DWT is so sensitive to the channel noise as shown in the articles [4][5].To solve this problem we are going to analyze data during transmission to discover what is the most important parts that can make the difference in the quality or received image by doing lot of tests in transmitted indices according to the decomposed levels provided by discrete wavelet transform.The paper is organized as follow: In the first part we will introduce the compression using vector quantization and discrete wavelet transform. The second part the effect of the channel noise in image compressed with vector quantization and discrete wavelet transform. In third part the effect of the channel noise in each level generated by discrete wavelet transform with different BER. In the fourth part we will divide each level to eight sublevels finally we try to propose some solutions according to the orbited results to that can enhance the quality of received image.

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Efficient JPEG 2000 Image Compression Scheme for Multihop Wireless Networks

Abstract: Abstrak

Cited by 15 publications

References 10 publications

An adaptive intelligent alarm system for wireless sensor network

An adaptive intelligent alarm system for wireless sensor network

Distributed Image Compression Architecture over Wireless Multimedia Sensor Networks

Data analysis for image transmitted using Discrete Wavelet Transform and Vector Quantization compression

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