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Vision, Image and Signal Processing, IEE Proceedings -

Issue 4 • Date 22 Aug. 2003

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Displaying Results 1 - 9 of 9
  • Compression of image block means for non-equal block partition schemes using Delaunay triangulation and prediction

    Page(s): 239 - 243
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (925 KB)  

    An approach based on applying Delaunay triangulation to the compression of mean values of image blocks that have non-identical shape and size is proposed. It can be useful for image compression methods that require the use of image partition schemes with non-equal block sizes, such as fractal and DCT-based image coding. Some aspects of practical realisation of the proposed method are discussed. Evaluation of the performance of the proposed method is carried out and comparisons with some conventional methods are made, demonstrating the potential of the method. View full abstract»

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  • Neural minor component analysis approach to robust constrained beamforming

    Page(s): 205 - 218
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (412 KB)  

    Since the pioneering work of S.-I. Amari (1977) and E. Oja (1982; 1989; 1992), principal component neural networks and their extensions have become an active adaptive signal processing research field. One of such extensions is minor component analysis (MCA), that proves to be effective in tasks such as robust curve/surface fitting and noise reduction. The aims of the paper are to give a detailed and homogeneous review of one-unit first minor/principal component analysis and to propose an application to robust constrained beamforming. In particular, after a careful presentation of first/minor component analysis algorithms based on a single adaptive neuron, along with relevant convergence/steady-state theorems, it is shown how the adaptive robust constrained beamforming theory by H. Cox et al. (see IEEE Trans. Acoust. Speech. Sig. Process., vol.34, no.3, p.393-8, 1986; vol.35, no.10, p.1365-76, 1987) may be advantageously recast into an MCA setting. Experimental results obtained with a triangular array of microphones introduced in a teleconference context help to assess the usefulness of the proposed theory. View full abstract»

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  • Low-power data-dependent 8×8 DCT/IDCT for video compression

    Page(s): 245 - 255
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (691 KB)  

    Traditional fast discrete cosine transform (DCT)/inverse DCT (IDCT) algorithms have focused on reducing arithmetic complexity and have fixed run-time complexities regardless of the input. Recently, data-dependent signal processing has been applied to the DCT/IDCT. These algorithms have variable run-time complexities. A two-dimensional 8×8 low-power DCT/IDCT design is implemented using VHDL by applying the data-dependent signal processing concept onto the traditional fixed-complexity fast DCT/IDCT algorithm. To reduce power, the design is based on Loeffler's fast algorithm, which uses a low number of multiplications. On top of that, zero bypassing, data segmentation, input truncation and hardwired canonical sign-digit (CSD) multipliers are used to reduce the run-time computation, hence reducing the switching activities and the power. When synthesised using CMC 0.18 μm 1.6 V CMOSP technology, the proposed FDCT/IDCT design consumes 8.94/9.54 mW, respectively, with a clock frequency of 40 MHz and a processing rate of 320 Msample/s. This design features lower dynamic power consumption per sample, i.e. it is more power-efficient than other previously reported high-performance FDCT/IDCT designs. View full abstract»

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  • Vector area morphology for motion field smoothing and interpretation

    Page(s): 219 - 226
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (733 KB)  

    A new nonlinear technique for filtering motion fields and other multivariate data is introduced. The method is developed from mathematical morphological area openings and uses a vector-to-scalar transform, in which each vector is replaced by the sum of the distances to its connected neighbours, to control the growth of extrema regions. As the filter either perfectly preserves or completely removes image components, it is able to remove noise without altering significant features. In addition, at larger area sizes, a meaningful interpretation of the underlying structure is achieved. Results show that the vector area morphology sieve performs well in comparison to the widely used vector median filter. View full abstract»

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  • Region-growing approach to colour segmentation using 3D clustering and relaxation labelling

    Page(s): 270 - 276
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1763 KB)  

    The paper presents a new segmentation algorithm for colour images based on a series of region growing and merging processes. This algorithm starts with the region growing process, which groups pixels into homogeneous regions by combining 3D clustering and relaxation labelling techniques. Each resulting small region is then merged to the region which is the nearest to it in terms of colour similarity and spatial proximity. One problem with region growing is its inherent dependency on the selection of the seed region, which can be avoided by using the relaxation labelling technique. Experimental results are presented to demonstrate the performance of the new method in terms of better segmentation and less sensitivity to noise, and in terms of computational efficiency. The segmentation results using the fuzzy c-means technique, the competitive learning neural network and a region growing and merging algorithm are also presented for comparison purposes. View full abstract»

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  • Hybrid Golomb codes for a group of quantised GG sources

    Page(s): 256 - 260
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (252 KB)  

    The authors develop a class of codes for quantised generalised Gaussian (GG) sources. This new class of codes, that are called hybrid Golomb (HG) codes, are hybrids of Golomb-Rice (GR) codes and exp-Golomb (EG) codes. They integrate the properties of both GR and EG codes, which makes their performance more robust under variable source parameters. The efficiencies of the three classes of codes are compared and it is shown that the set of HG codes have efficiencies of approximately 70% or greater for a wide range of parameter values, whereas GR and EG codes can have efficiencies lower than 20%. The efficiencies of the set of HG codes are also compared with the set of EG codes that have the best performance under parameter scaling. It is shown that this set of HG codes still achieve a higher efficiency. View full abstract»

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  • Adaptive data hiding based on VQ compressed images

    Page(s): 233 - 238
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (700 KB)  

    Data hiding involves embedding secret data into various forms of digital media such as text, image, audio, and video. With the rapid growth of network communication, data-hiding techniques are widely used in protecting copyright, embedding captions and communicating secretly. The authors propose an adaptive algorithm to embed data into VQ compressed images. This method adaptively varies the embedding process according to the amount of hidden data. The proposed method provides more effective hiding and higher quality images than conventional methods. The results of experimental comparisons are also presented. View full abstract»

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  • Area-time efficient between-class variance module for adaptive segmentation process

    Page(s): 263 - 269
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (503 KB)  

    Adaptive progressive thresholding (APT) has been shown to be an efficient method to segment the lumen region of endoscopic images. A pipelined architecture was previously proposed in an attempt to accelerate the conventional APT in hardware. A novel architecture for the between-class variance computations of APT is presented to minimise the severe bottleneck of the iterative loop in the APT process. The technique employs binary logarithm conversion to eliminate the computationally intensive dividers and reduce the complexity of the multipliers of the previous architecture. The proposed method employs a reconfigurable logarithmic computing unit, which can be configured to achieve a highly accurate between-class variance unit. It has been shown that the proposed approach leads to an area-time efficient FPGA implementation which is capable of a computation speed-up of ∼2.75 times while occupying only one-sixth of the number of slices required by the previous approach. View full abstract»

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  • Popular biorthogonal wavelet filters via a lifting scheme and its application in image compression

    Page(s): 227 - 232
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (242 KB)  

    A technique using a lifting scheme is presented for constructing compactly supported wavelets whose coefficients are composed of free variables locating in an interval. An efficient approach-based wavelet for image compression is developed by selecting the coefficients of the 9-7 wavelet filter and associated lifting scheme. Furthermore, the rationalised coefficients wavelet filter that can be implemented with simple integer arithmetic is achieved and its characteristic is close to the well known original irrational coefficients 9-7 wavelet filters developed by A. Cohen et al. (Commun. Pure Appl. Maths., vol.45, no.1, p.485-560, 1992). To reduce the computational cost of image coding applications further, an acceleration technique is proposed for the lifting steps. Software and hardware simulations show that the new method has very low complexity, and simultaneously preserves the high quality of the compressed image. View full abstract»

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