Journal of Real-Time Image Processing

Publisher: Springer Verlag

Journal description

Current impact factor: 2.02

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 1.111
2012 Impact Factor 1.156
2011 Impact Factor 1.02
2010 Impact Factor 0.962

Impact factor over time

Impact factor

Additional details

5-year impact 1.06
Cited half-life 3.70
Immediacy index 0.10
Eigenfactor 0.00
Article influence 0.43
Other titles Real-time image processing
ISSN 1861-8200
OCLC 73532162
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Springer Verlag

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    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: In the last two decades, we have seen an amazing development of image processing techniques targeted for medical applications. We propose multi-GPU-based parallel real-time algorithms for segmentation and shape-based object detection, aiming at accelerating two medical image processing methods: automated blood detection in wireless capsule endoscopy (WCE) images and automated bright lesion detection in retinal fundus images. In the former method we identified segmentation and object detection as being responsible for consuming most of the global processing time. While in the latter, as segmentation was not used, shape-based object detection was the compute-intensive task identified. Experimental results show that the accelerated method running on multi-GPU systems for blood detection in WCE images is on average 265 times faster than the original CPU version and is able to process 344 frames per second. By applying the multi-GPU framework for bright lesion detection in fundus images we are able to process 62 frames per second with a speedup average 667 times faster than the equivalent CPU version.
    Journal of Real-Time Image Processing 07/2015; DOI:10.1007/s11554-015-0517-3
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    ABSTRACT: Recent computer systems and handheld devices are equipped with high computing capability, such as general purpose GPUs (GPGPU) and multi-core CPUs. Utilizing such resources for computation has become a general trend, making their availability an important issue for the real-time aspect. Discrete cosine transform (DCT) and quantization are two major operations in image compression standards that require complex computations. In this paper, we develop an efficient parallel implementation of the forward DCT and quantization algorithms for JPEG image compression using Open Computing Language (OpenCL). This OpenCL-based parallel implementation utilizes a multi-core CPU and a GPGPU to perform DCT and quantization computations. We demonstrate the capability of this design via two proposed working scenarios. The proposed approach also applies certain optimization techniques to improve the kernel execution time and data movements. We developed an optimal OpenCL kernel for a particular device using device-based optimization factors, such as thread granularity, work-items mapping, workload allocation, and vector-based memory access. We evaluated the performance in a heterogeneous environment, finding that the proposed parallel implementation was able to speed up the execution time of the DCT and quantization by factors of 7.97 and 8.65, respectively, obtained from 1024 × 1024 and 2084 × 2048 image sizes in 4:4:4 format.
    Journal of Real-Time Image Processing 05/2015; DOI:10.1007/s11554-015-0507-5
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    ABSTRACT: The MPEG has recently Querydeveloped a new standard, MPEG media transport (MMT), for the next-generation hybrid media delivery service over IP networks considering the emerging convergence of digital broadcast and broadband services. On account of the heterogeneous characteristics of broadcast and broadband networks, MMT provides an efficient delivery timing model to enable inter-network synchronization, measure various kinds of transmission delays and jitters caused by the transmission delay, and re-adjust the timing relationship between the MMT packets to ensure synchronized playback. By exploiting the delivery timing model, it is possible to accurately estimate the round-trip time (RTT) experienced during MMT packet transmission. Based on the measured RTT, we propose an efficient delay-constrained automatic repeat request (ARQ) scheme, which is applicable to MMT packet-based real-time video streaming service over IP networks. In the proposed ARQ scheme, the receiver buffer fullness at the time of packet loss detection is used to compute the arrival deadline, which is the maximum allowed time for completing the requesting and retransmitting of the lost MMT packet. Simulation results demonstrate that the proposed delay-constrained ARQ scheme can not only provide reliable error recovery, but it also achieves significant bandwidth savings by reducing the number of wastefully retransmitted packets that arrive at the receiver side and exceed the allowed arrival deadline.
    Journal of Real-Time Image Processing 05/2015; DOI:10.1007/s11554-015-0503-9
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    ABSTRACT: Transmission of high efficiency video coding (HEVC) video streams over error-prone enterprise wireless local area networks (WLAN) architectures is challenging because of the difficulties in buffer overflow management in the switches within enterprise WLAN architectures. Thus, this paper proposes a new quality-aware video transmission method for company-wide enterprise WLAN architectures by combining video transmission technologies with a distributed stochastic buffering model that jointly controls power consumption and queue stabilization. After conducting extensive simulations with HEVC test sequences, significant video quality improvements are observed with the average Y-PSNR gain of 3.33 dB.
    Journal of Real-Time Image Processing 04/2015; DOI:10.1007/s11554-015-0501-y
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    ABSTRACT: This paper proposes a fast algorithm for integrating connected-component labeling and Euler number computation. Based on graph theory, the Euler number of a binary image in the proposed algorithm is calculated by counting the occurrences of four patterns of the mask for processing foreground pixels in the first scan of a connected-component labeling process, where these four patterns can be found directly without any additional calculation; thus, connected-component labeling and Euler number computation can be integrated more efficiently. Moreover, when computing the Euler number, unlike other conventional algorithms, the proposed algorithm does not need to process background pixels. Experimental results demonstrate that the proposed algorithm is much more efficient than conventional algorithms either for calculating the Euler number alone or simultaneously calculating the Euler number and labeling connected components.
    Journal of Real-Time Image Processing 04/2015; DOI:10.1007/s11554-015-0499-1
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    ABSTRACT: Wide-angle images gained a huge popularity in the last years due to the development of computational photography and imaging technological advances. They present the information of a scene in a way which is more natural for the human eye but, on the other hand, they introduce artifacts such as bent lines. These artifacts become more and more unnatural as the field of view increases. In this work, we present a technique aimed to improve the perceptual quality of panorama visualization. The main ingredients of our approach are, on one hand, considering the viewing sphere as a Riemann sphere, what makes natural the application of M\"obius (complex) transformations to the input image, and, on the other hand, a projection scheme which changes in function of the field of view used. We also introduce an implementation of our method, compare it against images produced with other methods and show that the transformations can be done in real-time, which makes our technique very appealing for new settings, as well as for existing interactive panorama applications.
    Journal of Real-Time Image Processing 04/2015; DOI:10.1007/s11554-015-0502-x
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    ABSTRACT: In this work, a clustering approach for bandwidth reduction in distributed smart camera networks is presented. Properties of the environment such as camera positions and environment pathways, as well as dynamics and features of targets are used to limit the flood of messages in the network. To better understand the correlation between camera positioning and pathways in the scene on one hand and temporal and spatial properties of targets on the other hand, and to devise a sound messaging infrastructure, a unifying probabilistic modeling for object association across multiple cameras with disjointed view is used. Communication is efficiently handled using a task-oriented node clustering that partition the network in different groups according to the pathway among cameras, and the appearance and temporal behavior of targets. We propose a novel asynchronous event exchange strategy to handle sporadic messages generated by non-frequent tasks in a distributed tracking application. Using a Xilinx-FPGA with embedded Microblaze processor, we could show that, with limited resource and speed, the embedded processor was able to sustain a high communication load, while performing complex image processing computations.
    Journal of Real-Time Image Processing 04/2015; DOI:10.1007/s11554-015-0498-2
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    ABSTRACT: The latest video coding standard, high efficiency video coding (HEVC), is developed to acquire a more efficient coding performance than the previous standard, H.264/AVC. To achieve this coding performance, elaborate coding tools were implemented in HEVC. Although those tools show a higher coding performance than H.264/AVC, the encoding complexity is heavily increased. Especially, motion estimation (ME) requires the most computational complexity because that is always performed on three inter-prediction modes: uni-directional prediction in List 0 (Uni-L0), uni-directional prediction in List 1 (Uni-L1), and bi-prediction (Bi). In this paper, we propose a priority-based inter-prediction mode decision method to reduce the complexity of ME caused by inter-prediction. The proposed method computes the priorities of all inter-prediction modes and decides whether ME is performed or not. Experimental results show that the proposed method reduces the computational complexity of ME up to 55.51% while maintaining similar coding performance compared to HEVC test model (HM) version 10.1.
    Journal of Real-Time Image Processing 03/2015; DOI:10.1007/s11554-015-0493-7
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    ABSTRACT: The Journal of Real-Time Image Processing is entering its 10th year of publication with a steady increase in its stature in the area of image processing. The number of downloads grew to 37K+ in 2014. There are currently six special issue calls for papers, which can be viewed in the back matter of this issue. In the past few years, changes have been made to the Editorial Board to incorporate the technological trends and challenges in the field of real-time image processing. In addition, to improve the geographical representation of manuscripts being submitted, changes are being made to the Advisory Board. As a first step, we are delighted to inform our readers that Professor Touradj Ebrahimi, who is a well-known researcher and technology leader with extensive experience in image processing, has kindly agreed to join the Advisory Board. It is a great pleasure to have him in our Advisory Board.The editorial board meeting of JRTIP (see Fig. 1) was recently held in San Francisco in Februar ...
    Journal of Real-Time Image Processing 03/2015; 10(1). DOI:10.1007/s11554-015-0491-9
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    ABSTRACT: A multiplierless pruned approximate eight-point discrete cosine transform (DCT) requiring only ten 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 \(8\times 8\) 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.
    Journal of Real-Time Image Processing 03/2015; DOI:10.1007/s11554-015-0492-8
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    ABSTRACT: Split and merge segmentation is a popular region-based segmentation scheme for its robustness and computational efficiency. But it is hard to realize for larger size images or video frames in real time due to its iterative sequential data flow pattern. A quad-tree data structure is quite popular for software implementation of the algorithm, where a local parallelism is difficult to establish due to inherent data dependency between processes. In this paper, we have proposed a parallel algorithm of splitting and merging which depends only on local operations. The algorithm is mapped onto a hierarchical cell network, which is a parallel version of Locally Excitory Globally Inhibitory Oscillatory Network (LEGION). Simulation results show that the proposed design is faster than any of the standard split and merge algorithmic implementations, without compromising segmentation quality. The timing performance enhancement is manifested in its Finite State Machine based VLSI implementation in VIRTEX series FPGA platforms. We have also shown that, though segmentation qualitywise split-and-merge algorithm is little bit behind the state-of-the-art algorithms, computational speedwise it over performs those sophisticated and complex algorithms. Good segmentation performance with minimal computational cost enables the proposed design to tackle real time segmentation problem in live video streams. In this paper, we have demonstrated live PAL video segmentation using VIRTEX 5 series FPGA. Moreover, we have extended our design to HD resolution for which the time taken is less than 5 ms rendering a processing throughput of 200 frames per second.
    Journal of Real-Time Image Processing 02/2015; DOI:10.1007/s11554-015-0488-4
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    ABSTRACT: The stereo to multi-view conversion technology plays an important role in the development and promotion of three-dimensional television, which can provide adequate supply of high-quality 3D content for autostereoscopic displays. This paper focuses on a real-time implementation of the stereo to multi-view conversion system, the major parts of which are adaptive meshing, sparse stereo correspondence, energy equation construction and virtual-view rendering. To achieve the real-time performance, we make three main contributions. First, we introduce adaptive meshing to reduce the computational complexity at the expense of slight decrease in quality. Second, we use a simple and effective method based on block matching algorithm to generate the sparse disparity map. Third, for the module of block-saliency calculation, sparse stereo correspondence and view synthesis, novel parallelization strategies and fine-grained optimization techniques based on graphic processing units are used to accelerate the executing speed. Experimental results show that the system can achieve real-time and semi-real-time performance when rendering 8 views with the image resolution of 1280 × 720 and 1920 × 1080 on Tesla K20. The images and videos presented finally are both visually realistic and comfortable.
    Journal of Real-Time Image Processing 02/2015; DOI:10.1007/s11554-015-0490-x