Repository logo
 

Search Results

Now showing 1 - 7 of 7
  • On ECG Signal Compression With 1-D Multiscale Recurrent Patterns Allied to Preprocessing Techniques
    Publication . Filho, E.B.L.; Rodrigues, N.M.M.; Silva, E.A.B. da; Carvalho, M.B. de; Faria, S.M.M. de; Silva, V.M.M. da; M. M. Rodrigues, Nuno; Faria, Sergio
    This paper presents the results of a multiscale pattern-matching-based ECG encoder, which employs simple preprocessing techniques for adapting the input signal. Experiments carried out with records from the Massachusetts Institute of Technology-Beth Israel Hospital database show that the proposed scheme is effective, outperforming some state-of-the-art schemes described in the literature.
  • Improving multiscale recurrent pattern image coding with least-squares prediction mode
    Publication . Graziosi, Danillo B.; Rodrigues, Nuno M. M.; Silva, Eduardo A. B. da; Faria, Sérgio M. M. de; Carvalho, Murilo B. de; Faria, Sergio; M. M. Rodrigues, Nuno;
    The Multidimensional Multiscale Parser-based (MMP) image coding algorithm, when combined with flexible partitioning and predictive coding techniques (MMP-FP), provides state-of-the-art performance. In this paper we investigate the use of adaptive least-squares prediction in MMP. The linear prediction coefficients implicitly embed the local texture characteristics, and are computed based on a block’s causal neighborhood (composed of already reconstructed data). Thus, the intra prediction mode is adaptively adjusted according to the local context and no extra overhead is needed for signaling the coefficients. We add this new context-adaptive linear prediction mode to the other MMP prediction modes, that are based on the ones used in H.264/AVC; the best mode is chosen through rate-distortion optimization. Simulation results show that least-squares prediction is able to significantly increase MMP-FPs rate-distortion performance for smooth images, leading to better results than the ones of state-of-theart, transform-based methods. Yet with the addition of least-squares prediction MMP-FP presents no performance loss when used for encoding non-smooth images, such as text and graphics.
  • Light field HEVC-based image coding using locally linear embedding and self-similarity compensated prediction
    Publication . Monteiro, Ricardo; Lucas, Luis; Conti, Caroline; Nunes, Paulo; M. M. Rodrigues, Nuno; Faria, Sergio; Pagliari, Carla; Silva, Eduardo da; Soares, Luis
    Light field imaging is a promising new technology that allows the user not only to change the focus and perspective after taking a picture, as well as to generate 3D content, among other applications. However, light field images are characterized by large amounts of data and there is a lack of coding tools to efficiently encode this type of content. Therefore, this paper proposes the addition of two new prediction tools to the HEVC framework, to improve its coding efficiency. The first tool is based on the local linear embedding-based prediction and the second one is based on the self-similarity compensated prediction. Experimental results show improvements over JPEG and HEVC in terms of average bitrate savings of 71.44% and 31.87%, and average PSNR gains of 4.73dB and 0.89dB, respectively.
  • Image Coding Using Generalized Predictors Based on Sparsity and Geometric Transformations
    Publication . Lucas, Luís F. R.; M. M. Rodrigues, Nuno; Silva, Eduardo A. B. da; Pagliari, Carla L.; Faria, Sergio
  • Optimized Reference Picture Selection for Light Field Image Coding
    Publication . Monteiro, J. S. Ricardo; Nunes, J. L. Paulo; M. M. Rodrigues, Nuno; Faria, Sergio
    This paper proposes a new reference picture selection method for light field image coding using the pseudovideo sequence (PVS) format. State-of-the-art solutions to encode light field images using the PVS format rely on video coding standards to exploit the inter-view redundancy between each sub-aperture image (SAI) that composes the light field. However, the PVS scanning order is not usually considered by the video codec. The proposed solution signals the PVS scanning order to the decoder, enabling implicit optimized reference picture selection for each specific scanning order. With the proposed method each reference picture is selected by minimizing the Euclidean distance to the current SAI being encoded. Experimental results show that, for the same PVS scanning order, the proposed optimized reference picture selection codec outperforms HEVC video coding standard for light field image coding, up to 50% in terms of bitrate savings
  • Light Field Image Coding using High Order Prediction Training
    Publication . Monteiro, Ricardo J. S.; Nunes, Paulo J. L.; Faria, Sergio; M. M. Rodrigues, Nuno
    This paper proposes a new method for light field image coding relying on a high order prediction mode based on a training algorithm. The proposed approach is applied as an Intra prediction method based on a two-stage block-wise high order prediction model that supports geometric transformations up to eight degrees of freedom. Light field images comprise an array of micro-images that are related by complex perspective deformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low order translational prediction models. The proposed prediction mode is able to exploit the non-local spatial redundancy introduced by light field image structure and a training algorithm is applied on different micro-images that are available in the reference region aiming at reducing the amount of signaling data sent to the receiver. The training direction that generates the most efficient geometric transformation for the current block is determined in the encoder side and signaled to the decoder using an index. The decoder is therefore able to repeat the high order prediction training to generate the desired geometric transformation. Experimental results show bitrate savings up to 12.57% and 50.03% relatively to a light field image coding solution based on low order prediction without training and HEVC, respectively.
  • Intra Predictive Depth Map Coding Using Flexible Block Partitioning
    Publication . Lucas, Luis F. R.; Wegner, Krzysztof; M. M. Rodrigues, Nuno; Pagliari, Carla L.; Silva, Eduardo A. B. da; Faria, Sergio
    A complete encoding solution for efficient intra-based depth map compression is proposed in this paper. The algorithm, denominated predictive depth coding (PDC), was specifically developed to efficiently represent the characteristics of depth maps, mostly composed by smooth areas delimited by sharp edges. At its core, PDC involves a directional intra prediction framework and a straightforward residue coding method, combined with an optimized flexible block partitioning scheme. In order to improve the algorithm in the presence of depth edges that cannot be efficiently predicted by the directional modes, a constrained depth modeling mode, based on explicit edge representation, was developed. For residue coding, a simple and low complexity approach was investigated, using constant and linear residue modeling, depending on the prediction mode. The performance of the proposed intra depth map coding approach was evaluated based on the quality of the synthesized views using the encoded depth maps and original texture views. The experimental tests based on all intra configuration demonstrated the superior rate-distortion performance of PDC, with average bitrate savings of 6%, when compared with the current state-of-the-art intra depth map coding solution present in the 3D extension of a high-efficiency video coding (3D-HEVC) standard. By using view synthesis optimization in both PDC and 3D-HEVC encoders, the average bitrate savings increase to 14.3%. This suggests that the proposed method, without using transform-based residue coding, is an efficient alternative to the current 3D-HEVC algorithm for intra depth map coding.