Image compression algorithms in wireless multimedia sensor networks: A survey

WT5”BZ]The discrete wavelet transform (DWT) has been applied to signal processing systems However, special purpose hardware is needed to implement the huge computation of the DWT It is a key technique to design DWT chip for signal processing A VLSI architecture of the recursive pyramid algorithm (RPA) for the DWT is proposed By using a group of input delay units and a control unit, the DWT is implemented using only one set of parallel filters The Verilog HDL model of the architecture is simulated and synthesized [WT5HZ]

VLSI Implementation of Discrete Wavelet Transform

Wireless sensor networks are increasingly gaining attention. In recent years, a great deal of monitoring, control and tracking applications have been designed for different scenarios. For such networks, camera-enabled sensors can retrieve visual data from a monitored field, providing valuable information for many applications. In general, those networks have resource constraints of processing, memory, energy and transmission bandwidth, imposing many design challenges. Nevertheless, a group of applications may also have security requirements, which bring additional complexity to be handled. Most traditional security mechanisms for popular networks, like the Internet, are not suitable for wireless sensor networks, demanding proper investigation in this area. In this paper, we survey recent developments in encryption and privacy in wireless sensor networks deployed for transmissions of image snapshots, reviewing innovative approaches to provide different levels of security. Promising research directions are also discussed.

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A Survey of Image Security in Wireless Sensor Networks

Memristor-based hardware accelerators are gaining an increased attention as a potential candidate to speed-up the vector-matrix operations commonly needed in many digital image processing tasks due to their area, speed, and energy efficiency. In this paper, a memristor-based image compression (MR-IC) architecture that exploits a lossy 2-D discrete wavelet transform is proposed. The architecture is composed of a computational memristor crossbar, an intermediate memory array that stores the row-transformed coefficients and a final memory that holds the compressed version of the original image. The computational memristor array performs in-memory computation on the initially stored transformation coefficients. Using the quantitative analysis approach, we demonstrate a $10\times $ reduction in a number of operations compared with a conventional application-specific integrated circuit implementation. This translates to five orders of magnitude reduction in area, around $11\times $ improvement in energy efficiency, and $1.28\times $ speedup in computation time. Image quality metrics, such as peak signal-to-noise ratio (PSNR), structural similarity (SSIM) index, and complex wavelet-SSIM (CW-SSIM), are used to quantify the reduction in image quality due to lossy compression. The achieved metrics for conventional versus MR-IC are: PSNR 57.24 versus 33.29 dB, SSIM 0.9994 versus 0.8853, and CW-SSIM 1 versus 0.9983. Simulation results show that the 32 quantization levels proposed architecture provides significant improvements in energy, area, and performance compared to the 32 levels CMOS implementation with comparable CW-SSIM.

Memristor-Based Hardware Accelerator for Image Compression

Wireless multimedia sensor network (WMSN) comprising of miniature sensor nodes is capable of processing multimedia data traffic such as still images and video from the environment. There is a wide range of applications which get benefited from such network. Unprocessed multimedia transmission is always expensive in terms of processing power, storage, and bandwidth. So, data processing is a challenge in WMSN. Exploring low-overhead data compression technique is a solution towards this problem. In this work we propose an energy saving image compression technique for WMSN using curve fitting technique considering the application of post-disaster situation analysis through image capturing of the affected area. Upon employing the method on the macroblocks of sensory image, curve fitting coefficients are generated and transmitted towards the sink thereby saves energy by transmitting reduced volume of data. Finally the design feasibility along with simulation results including statistical analysis is presented to evaluate efficacy of the scheme in terms of two conflicting parameters viz. energy consumption and peak signal to noise ratio. The comparative results confirm our scheme’s supremacy in WMSN application domain over existing methods.

An energy efficient image compression scheme for wireless multimedia sensor network using curve fitting technique

Multidimensional sensors, such as digital camera sensors in the visual sensor networks VSNs generate a huge amount of information compared with the scalar sensors in the wireless sensor networks WSNs. Processing and transmitting such data from low power sensor nodes is a challenging issue through their limited computational and restricted bandwidth requirements in a hardware constrained environment. Source coding can be used to reduce the size of vision data collected by the sensor nodes before sending it to its destination. With image compression, a more efficient method of processing and transmission can be obtained by removing the redundant information from the captured image raw data. In this paper, a survey of the main types of the conventional state of the art image compression standards such as JPEG and JPEG2000 is provided. A literature review of their advantages and shortcomings of the application of these algorithms in the VSN hardware environment is specified. Moreover, the main factors influencing the design of compression algorithms in the context of VSN are presented. The selected compression algorithm may have some hardware-oriented properties such as; simplicity in coding, low memory need, low computational load, and high-compression rate. In this survey paper, an energy efficient hardware based image compression is highly requested to counter the severe hardware constraints in the WSNs.

Efficient Hardware-Based Image Compression Schemes for Wireless Sensor Networks: A Survey

One major complication in implementing the discrete two-dimensional wavelet transform to a platform with limited resources is the need for huge memory This paper addresses memory-efficient implementation of the wavelet-based image coding requirements These requirements are usually distinct by resource-limited platforms such as tiny wireless sensors, which may build a wireless sensor network (WSN) Moreover, the bulky image data provided by the cameras combined with the network's resource constraints require discovering new means for data processing and communication Image coding with scalar quantization on hierarchical structures of the transformed wavelet is considerably valuable and computationally simple Typically, this is a case of set partitioning in hierarchical trees (SPIHT) a highly refined version of Embedded Zerotree Wavelet (EZW) structure that results from data similarity across different sub-bands The paper deals with the effectiveness of an appropriate wavelet filter type that performs best results for SPIHT algorithm The implementation of SPIHT structure based on the lifting scheme of wavelets is designed to compress several gray scale images with different information content in the MATLAB environment Subjective and objective results are also evaluated and examined

http://ieeexplore.ieee.org/iel7/6476082/6487099/06487130.pdf

The most proper wavelet filters in low-complexity and an embedded hierarchical image compression structures for wireless sensor network implementation requirements

Several primary concern points should be deliberated in the wireless sensor network WSN design When the networks are included with cameras, limitation in the image data sizes pose as a new problem Hence there is a necessity to find new ways for data processing and communication If the size of data could be minimized, image compression would reduce the memory requirement and thus communication costs Recently, transform-based image compression methods are still very attractive and popular These methods are mainly based either on Discrete Cosine Transform DCT such as the Joint Photographic Experts Group JPEG or Discrete Wavelet Transform DWT such as JPEG2000 DCT based algorithms are fast with low-complexity and low-memory However, they often cause annoying blocking artifacts in the low bit rate transmission The low complexity embedded DWT-based coders generate a bitstream that can be decoded at multiple transmission bit rates with an acceptable quality of the reconstructed image at the reception Set Partitioning in Hierarchical Trees SPIHT is among the most popular quality-scalable wavelet based image coders In this paper, the lifting scheme LS implementation of wavelets is also investigated before the set-partitioning coding is applied to compress the images However, with fewer bits to transmit using the SPIHT coder results, this technique will be suitable to restricted property with limited resources platforms

Low complexity image compression architecture based on lifting wavelet transform and embedded hierarchical structures

In this paper, flexible hardware architecture of multi-level decomposition Discrete Wavelet Transform (DWT) is proposed for image compression applications to eliminate redundant information from the transmitted images or video frames over the wireless channel. This architecture of DWT is described and synthesized with the Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) based methodology. The design can be accommodated on any targeting Field Programmable Gate Array (FPGA) device with slight changes. It facilitates to images of size 64×64, 128×128, 256×256, and 512× 512 pixels and capable of seven levels of decomposition. In order to reduce computational complexities, Fast Haar Wavelet Transform (FHWT) is used. The reduction in the resource usage of this 2D DWT multilevel FPGA core can be used to counter severe hardware constraints of various wireless and mobile device applications.

Multilevel decomposition Discrete Wavelet Transform for hardware image compression architectures applications

The HD-W60 microcontroller is an open source prototype electronic platform using HD2016 software package. The proposed system consists of a Light Emitting Diode (LED) array, as well as a circuit for connecting to a computer through USB or wireless connectivity, it also comprises a computer application for controlling the display of characters or graphics on the screen. Because the display is made up of small independent modules, this work proposes an efficient and scalable solution in which the size of the display can be extended along the rows and columns without changing the circuit. This paper will deliberate on displaying a scrolling text message on a 96×32 LED dot matrix display which consists of 24 boards of (8×16 LED matrix). The developed system is determined to be suitable for a variety of other Wi Fi applications, as well as the additional features that may be incorporated in Hypertext (Graphics Interchange Format GIF - Picture Format, Animation Character, (shock wave flash) SWF Video) further designs.

Khamees Khalaf Hasan

Papers

Efficient Hardware-Based Image Compression Schemes for Wireless Sensor Networks: A Survey

The most proper wavelet filters in low-complexity and an embedded hierarchical image compression structures for wireless sensor network implementation requirements

Low complexity image compression architecture based on lifting wavelet transform and embedded hierarchical structures

Multilevel decomposition Discrete Wavelet Transform for hardware image compression architectures applications

Design and Enforcements of Wireless Based Matrix LED Message Moving Display by HD-W60 Microcontroller