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- On ECG Signal Compression With 1-D Multiscale Recurrent Patterns Allied to Preprocessing TechniquesPublication . 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, SergioThis 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 modePublication . 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.
- Video transcoding from H.264/AVC to MPEG-2 with reduced computational complexityPublication . Moiron, Sandro; Faria, Sergio; Navarro, António; Silva, Vitor; Assunção, PedroThis paper addresses video transcoding from H.264/AVC into MPEG-2 with reduced complexity and high rate-distortion efficiency. While the overall concept is based on a cascaded decoder-encoder, the novel adaptation methods developed in this work have the advantage of providing very good performance in H.264/AVC to MPEG-2 transcoding. The proposed approach exploits the similarities between the coding tools used in both standards, with the objective of obtaining a computationally efficient transcoder without penalising the signal quality. Fast and efficient methods are devised for conversion of macroblock coding modes and translation of motion information in order to compute the MPEG-2 coding format with a reduced number of operations, by reusing the corresponding data embedded in the incoming H.264/AVC coded stream. In comparison with a cascaded decoder-encoder, the fast transcoder achieves computational complexity savings up to 60% with slightly better peak signal-to-noise ratio (PSNR) at the same bitrate.
- Light field HEVC-based image coding using locally linear embedding and self-similarity compensated predictionPublication . Monteiro, Ricardo; Lucas, Luis; Conti, Caroline; Nunes, Paulo; M. M. Rodrigues, Nuno; Faria, Sergio; Pagliari, Carla; Silva, Eduardo da; Soares, LuisLight 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 TransformationsPublication . 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 CodingPublication . Monteiro, J. S. Ricardo; Nunes, J. L. Paulo; M. M. Rodrigues, Nuno; Faria, SergioThis 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
- Reconstruction of lost depth data in multiview video-plus-depth communications using geometric transformsPublication . Marcelino, Sylvain; Soares, Salviano; Faria, Sergio; Assunção, PedroThis paper addresses depth data recovery in multiview video-plus-depth communications affected by transmission errors and/or packet loss. The novel aspects of the proposed method rely on the use of geometric transforms and warping vectors, capable of capturing complex motion and view-dependent deformations, which are not efficiently handled by traditional motion and/or disparity compensation methods. By exploiting the geometric nature of depth information, a region matching approach combined with depth contour reconstruction is devised to achieve accurate interpolation of arbitrary shapes within lost regions of depth maps. The simulation results show that, for different packet loss rates, up to 20%, the depth maps recovered by the proposed method produce virtual views with better quality than existing methods based on motion information and spatial interpolation. An average PSNR gain of 1.48 dB is obtained in virtual views synthesised from depth maps using the proposed method.
- Light Field Image Coding Based on Hybrid Data RepresentationPublication . Monteiro, Ricardo J. S.; Rodrigues, Nuno M. M.; Faria, Sérgio M.M.; Nunes, Paulo J. L.This paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited, as is demonstrated. This novel hybrid data representation approach allows to simultaneously exploit four types of redundancies: i) sub-aperture image intra spatial redundancy, ii) sub-aperture image inter-view redundancy, iii) intra-micro-image redundancy, and iv) inter-micro-image redundancy between neighboring micro-images. The proposed light field coding solution allows flexibility for several types of baselines, by adaptively exploiting the most predominant type of redundancy on a coding block basis. To demonstrate the efficiency of using a hybrid representation, this paper proposes a set of efficient pixel prediction methods combined with a pseudo-video sequence coding approach, based on the HEVC standard. Experimental results show consistent average bitrate savings when the proposed codec is compared to relevant state-ofthe-art benchmarks. For lenslet light field content, the proposed coding algorithm outperforms the HEVCbased pseudo-video sequence coding benchmark by an average bitrate savings of 23%. It is shown for the same light field content that the proposed solution outperforms JPEG Pleno verification models MuLE and WaSP, as these codecs are only able to achieve 11% and −14% bitrate savings over the same HEVC-based benchmark, respectively. The performance of the proposed coding approach is also validated for light fields with wider baselines, captured with high-density camera arrays, being able to outperform both the HEVCbased benchmark, as well as MuLE and WaSP.
- Geometric transforms and reference picture list optimization for efficient disparity compensationPublication . Ricardo J. S. Monteiro; M. M. Rodrigues, Nuno; Faria, SergioThis paper presents a method to increase the efficiency of the disparity compensation process performed by state-of-the-art video coding extensions for 3D and multiview. Disparity compensation relies traditionally on a block matching algorithm limited to two degrees of freedom, that in many cases does not adequately address the disparity created by the camera arrays. The proposed method is combined with MV-HEVC in order to improve the efficiency of inter-frame prediction, by generating additional reference pictures, using 3D scene information. The new geometrically compensated pictures are chosen and reordered based on their usefulness for prediction and associated cost in the encoding process. When compared to MV-HEVC, the proposed scheme is able to achieve bitrate savings of up to 3.19% for convergent camera arrangements and 2.41% for parallel camera arrangements.
- Contributions to lossless coding of medical images using minimum rate predictorsPublication . Joao M. Santos; Guarda, André; M. M. Rodrigues, Nuno; Faria, SergioMedical imaging compression is experiencing a growth in terms of usage and image resolution, namely in diagnostics systems that require a large set of images, like MRI or CT. Furthermore, legal and diagnosis restrictions impose the use of lossless compression and data archival for several years. These facts create a demand for more efficient compression tools, used for archiving and communication. In this work, we first evaluate the performance of traditional medical image compression algorithms against that of recent state of the art lossless image encoders. We then propose a method to improve the Minimum Rate Predictors lossless encoder, by exploiting inter picture redundancy in volumetric anatomical images. Results show that the proposed method is more efficient than state of the art encoders, such as HEVC, by about 28.8%, and achieves a gain of up to 57.8% in compression ratio when compared with traditional methods.