Spatial Domain

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The Experts below are selected from a list of 146757 Experts worldwide ranked by ideXlab platform

Devert Wicker - One of the best experts on this subject based on the ideXlab platform.

  • A Spatial-Domain multiresolutional particle filter with thresholded wavelets
    Signal Processing, 2007
    Co-Authors: Lang Hong, Devert Wicker
    Abstract:

    Particle filters have been proven to be very effective for nonlinear/non-Gaussian filtering. However, the most notorious disadvantage of a particle filter is its formidable computational complexity, since hundreds (even thousands) of particles are usually needed to achieve a required approximation accuracy. It has also been proven that one of the techniques of truly solving a computational problem is multiresolutional processing, both in temporal and Spatial Domains. Therefore, in this paper we propose a multiresolutional particle filter in the Spatial Domain using thresholded wavelets to reduce significantly the number of particles, meanwhile maintaining the full strength of a particle filter.

Lang Hong - One of the best experts on this subject based on the ideXlab platform.

  • A Spatial Domain multiresolutional particle filter
    2007 Mediterranean Conference on Control & Automation, 2007
    Co-Authors: Lang Hong, Kefu Xue
    Abstract:

    Particle filters have been proven to be very effective for nonlinear/non-Gaussian filtering. However, the most notorious disadvantage of a particle filter is its formidable computational complexity, since hundreds (even thousands) of particles are usually needed to achieve a required approximation accuracy. It has also been proven that one of the techniques of truly solving a computational problem is multiresolutional processing, both in temporal and Spatial Domains. Therefore, in this paper we propose a multiresolutional particle filter in the Spatial Domain using thresholded wavelets to reduce significantly the number of particles, meanwhile maintaining the full strength of a particle filter.

  • A Spatial-Domain multiresolutional particle filter with thresholded wavelets
    Signal Processing, 2007
    Co-Authors: Lang Hong, Devert Wicker
    Abstract:

    Particle filters have been proven to be very effective for nonlinear/non-Gaussian filtering. However, the most notorious disadvantage of a particle filter is its formidable computational complexity, since hundreds (even thousands) of particles are usually needed to achieve a required approximation accuracy. It has also been proven that one of the techniques of truly solving a computational problem is multiresolutional processing, both in temporal and Spatial Domains. Therefore, in this paper we propose a multiresolutional particle filter in the Spatial Domain using thresholded wavelets to reduce significantly the number of particles, meanwhile maintaining the full strength of a particle filter.

Arjen P De Vries - One of the best experts on this subject based on the ideXlab platform.

  • geo Spatial Domain expertise in microblogs
    European Conference on Information Retrieval, 2014
    Co-Authors: Carsten Eickhoff, Arjen P De Vries
    Abstract:

    In this paper, we present a framework for describing a user's geo-Spatial Domain expertise in microblog settings. We investigate a novel way of casting the expertise problem by using points of interest POI as a possible categorization of expertise. To this end, we study a large-scale sample of geo-tagged tweets and model users' location tracks in order to gain insights into their daily activities and competencies. Based on a qualitative user study among active Twitter users, we present an initial exploration of Domain expertise indicators on microblogging portals and design a classification scheme that is able to reliably identify Domain experts.

  • ECIR - Geo-Spatial Domain Expertise in Microblogs
    Lecture Notes in Computer Science, 2014
    Co-Authors: Carsten Eickhoff, Arjen P De Vries
    Abstract:

    In this paper, we present a framework for describing a user's geo-Spatial Domain expertise in microblog settings. We investigate a novel way of casting the expertise problem by using points of interest POI as a possible categorization of expertise. To this end, we study a large-scale sample of geo-tagged tweets and model users' location tracks in order to gain insights into their daily activities and competencies. Based on a qualitative user study among active Twitter users, we present an initial exploration of Domain expertise indicators on microblogging portals and design a classification scheme that is able to reliably identify Domain experts.

Mehdi Hussain - One of the best experts on this subject based on the ideXlab platform.

  • image steganography in Spatial Domain a survey
    Signal Processing-image Communication, 2018
    Co-Authors: Mehdi Hussain, Ainuddin Wahid Abdul Wahab, Yamani Idna Bin Idris, Kihyun Jung
    Abstract:

    Abstract This paper presents a literature review of image steganography techniques in the Spatial Domain for last 5 years. The research community has already done lots of noteworthy research in image steganography. Even though it is interesting to highlight that the existing embedding techniques may not be perfect, the objective of this paper is to provide a comprehensive survey and to highlight the pros and cons of existing up-to-date techniques for researchers that are involved in the designing of image steganographic system. In this article, the general structure of the steganographic system and classifications of image steganographic techniques with its properties in Spatial Domain are exploited. Furthermore, different performance matrices and steganalysis detection attacks are also discussed. The paper concludes with recommendations and good practices drawn from the reviewed techniques.

  • Spatial Domain lossless image data compression method
    2011 International Conference on Information and Communication Technologies, 2011
    Co-Authors: Syed Ali Hassan, Mehdi Hussain
    Abstract:

    Images has very significant role in digital media. However, generally digital imaging generates large amounts of data it need to be compressed, without loss of relevant information or simply lossless compression. This paper presents a novel lossless image compression technique in Spatial Domain. The proposed algorithm divide the image into no. of blocks uses variable bits to store each block pixels. Calculation of variable bits is dependent on pixel values of each block. The advantage of proposed scheme, it is dependent upon pixels correlation with in a block. Experimental results show that our proposed algorithm gives better compression efficiency as compared to many existing state-of-the-art lossless Spatial Domain image compression algorithms such as LZW, RLE and DEFLATE used in TIFF, GIF and PNG formats.

Liu Decheng - One of the best experts on this subject based on the ideXlab platform.

  • A blind image watermarking scheme combining Spatial Domain and frequency Domain
    The Visual Computer, 2020
    Co-Authors: Yuan Zihan, Liu Decheng, Xueting Zhang
    Abstract:

    In order to realize the copyright protection of color image effectively, combining the advantages of Spatial-Domain watermarking scheme and frequency-Domain one, a blind color image watermarking scheme with high performance in the Spatial Domain is proposed in the paper. The presented scheme does not require real discrete cosine transform (DCT) and discrete Hartley transform (DHT), but only uses the different quantization steps to complete the embedding and blind extracting of color watermark in the Spatial Domain according to the unique characteristic of direct current (DC) components of DCT and DHT. The contributions of this paper include the following: (1) This scheme combined the strengths of watermarking scheme in the Spatial Domain and frequency Domain, which has fast speed and strong robustness; (2) the scheme makes full use of the energy aggregation characteristics of image block, and the invisibility of the watermarking scheme has greatly improved; and (3) different quantization steps are chosen to embed and extract watermark in different layers, which reduce the modification range of pixel value effectively. The experimental results show that compared with the existing schemes, the proposed watermarking scheme has higher performance, such as better invisibility, stronger robustness and shorter execution time.

  • New Rapid and Robust Color Image Watermarking Technique in Spatial Domain
    IEEE Access, 2019
    Co-Authors: Liu Decheng, Yuan Zihan, Gang Wang, Xiaofeng Zhang, Beijing Chen, Tao Yao
    Abstract:

    In this paper, a novel Spatial Domain color image watermarking technique is proposed to rapidly and effectively protect the copyright of the color image. First, the direct current (DC) coefficient of 2D-DFT obtained in the Spatial Domain is discussed, and the relationship between the change of each pixel in the Spatial Domain and the change of the DC coefficient in the Fourier transform is proved. Then, the DC coefficient is used to embed and extract watermark in the Spatial Domain by the proposed quantization technique. The novelties of this paper include three points: 1) the DC coefficient of 2D-DFT is obtained in the Spatial Domain without of the true 2D-DFT; 2) the relationship between the change of each pixel in the image block and the change of the DC coefficient of 2D-DFT is found, and; 3) the proposed method has the short running time and strong robustness. The experimental results on two publicly available image databases (CVG-UGR and USC-SIPI) have shown that the proposed method not only has satisfied the needs of invisibility but also has better performance in terms of robustness and real-time feature, which show the proposed method has both advantages of Spatial Domain and frequency Domain.