Low complexity DCT for image compression in wireless visual sensor networks

Kouadria, Nasreddine; Doghmane, Noureddine; Messadeg, Djemil; Harize, Saliha

doi:10.1049/el.2013.2781

Cited by 26 publications

(16 citation statements)

References 8 publications

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“…The MRDCT and BAS-2008 were selected in accordance to the discussion in previous section. The BAS-2013 was also included because it is the base for the only pruned approximate DCT competitor in literature [47]. Such designs were realized in a separable 2-D block transform using two 1-D transform blocks with a transpose buffer between them.…”

Section: Vlsi Architecturesmentioning

confidence: 99%

Energy-Efficient 8-Point DCT Approximations: Theory and Hardware Architectures

Cintra

Bayer

Coutinho

et al. 2015

Circuits Syst Signal Process

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Due to its remarkable energy compaction properties, the discrete cosine transform (DCT) is employed in a multitude of compression standards, such as JPEG and H.265/HEVC. Several low-complexity integer approximations for the DCT have been proposed for both 1-D and 2-D signal analysis. The increasing demand for low-complexity, energy efficient methods require algorithms with even lower computational costs. In this paper, new 8-point DCT approximations with very low arithmetic complexity are presented. The new transforms are proposed based on pruning state-of-the-art DCT approximations. The proposed algorithms were assessed in terms of arithmetic complexity, energy retention capability, and image compression performance. In addition, a metric combining performance and computational complexity measures was proposed. Results showed good performance and extremely low computational complexity. Introduced algorithms were mapped into systolic-array digital architectures and physically realized as digital prototype circuits using FPGA technology and mapped to 45 nm CMOS technology. All hardware-related metrics showed low resource consumption of the proposed pruned approximate transforms. The best proposed transform according to the introduced metric presents a reduction in power consumption of 21-25%. KeywordsDCT approximation image compressionFPGA pruned transforms 1 IntroductionTransform-based methods are widely employed in digital signal processing applications [1]. In this context, the efficient computation of discrete transforms has constantly attracted community efforts and the proposition of fast algorithms [2]. In particular, the 8-point discrete cosine transform (DCT) has a proven record of scientific and industrial applications, as demonstrated by the multitude of image and video coding standards that adopt it, such as: JPEG [3], MPEG [4-6], H.261 [7,8], H.263 [5,9], H.264/AVC [10,11], and the recent high efficiency video coding (HEVC) [12,13]. The HEVC is capable of achieving high compression * Renato J. Cintra is with the Signal Processing ).performance at approximately half the bit rate required by its predecessor H.264/AVC with same image quality [13][14][15][16]. On the other hand, the HEVC requires a significantly higher computational complexity in terms of arithmetic operations [14-17], being 2-4 times more computationally costly than H.264/AVC [14,16].In this context, the efficient computation of the DCT is a venue for improving the performance of abovementioned codecs.Since its inception, several fast algorithms for the DCT have been proposed [18][19][20][21][22][23]. However, traditional algorithms aim at the computation of the exact DCT, which requires several multiplication operations. Additionally, several algorithms have achieved theoretical multiplicative complexity lower-bounds [21,24]. As a consequence, the progress in this area headed to approximate methods [25][26][27]. In some applications, a simple DCT approximation can provide meaningful results at low arithmetic complexity [28]. Thus, appro...

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Section: Vlsi Architecturesmentioning

confidence: 99%

Energy-Efficient 8-Point DCT Approximations: Theory and Hardware Architectures

Cintra

Bayer

Coutinho

et al. 2015

Circuits Syst Signal Process

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“…Such method was applied in the context of voltage scaling for low-power dissipation. In the context of low-powered wireless vision sensor networks, a pruned approximate DCT was proposed in [40] based on the DCT approximation theory advanced in [20]. In [41] the pruning terminology was employed in a different context.…”

Section: Related Workmentioning

confidence: 99%

A multiplierless pruned DCT-like transformation for image and video compression that requires ten additions only

Coutinho

Cintra

Bayer

et al. 2015

J Real-Time Image Proc

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A multiplierless pruned approximate 8-point discrete cosine transform (DCT) requiring only 10 additions is introduced. The proposed algorithm was assessed in image and video compression, showing competitive performance with state-of-the-art methods. Digital synthesis in 45 nm CMOS technology up to place-and-route level indicates clock speed of 288 MHz at a 1.1 V supply. The 8 × 8 block rate is 36 MHz. The DCT approximation was embedded into HEVC reference software; resulting video frames, at up to 327 Hz for 8-bit RGB HEVC, presented negligible image degradation.

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“…On the other hand, being related to the more general Wireless Sensor Networks, VSNs have tight constraints in terms of computational, communication and energy resources. Thus, a huge part of the research on VSNs has been committed to finding efficient software solutions at every layer of the protocol stack, ranging from low-level communication protocols [1], [2], to multimedia compression schemes at the application layer [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

EZ-VSN: An Open-Source and Flexible Framework for Visual Sensor Networks

Bondi

Baroffio

Cesana

et al. 2016

IEEE Internet Things J.

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Abstract-We present a complete, open-source framework for rapid experimentation of Visual Sensor Networks (VSN) solutions. From the software point of view, we base our architecture on open-source and widely known C++ libraries to provide the basic image processing and networking primitives. The resulting system can be leveraged to create different types of VSNs, characterized by the presence of multiple cameras, relays and cooperator nodes, and can be run on any Linux-based hardware platform, such as the BeagleBone Black. To demonstrate the flexibility of the proposed framework, we describe two different application scenarios typical of VSNs, namely object recognition and parking monitoring. The framework is then used to evaluate the benefits of two complementary paradigms for networked visual analysis recently discussed in the literature. In the traditional Compress-then-Analyze (CTA) paradigm, compressed images are transmitted from camera nodes to a central controller, where they are analyzed. In the novel Analyze-then-Compress (ATC) paradigm, camera nodes extracts and compress local features from the acquired images. Such features are transmitted to the central controller and used to perform visual analysis. We show that the ATC paradigm outperforms CTA from the consumed energy point of view, at the same target analysis accuracy in both the application scenarios.

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Low complexity DCT for image compression in wireless visual sensor networks

Cited by 26 publications

References 8 publications

Energy-Efficient 8-Point DCT Approximations: Theory and Hardware Architectures

Energy-Efficient 8-Point DCT Approximations: Theory and Hardware Architectures

A multiplierless pruned DCT-like transformation for image and video compression that requires ten additions only

EZ-VSN: An Open-Source and Flexible Framework for Visual Sensor Networks

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