Percorrer por autor "Silva, Eduardo A. B. da"
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- Adaptive least squares prediction for stereo image codingPublication . Lucas, Luis F. R.; M. M. Rodrigues, Nuno; Silva, Eduardo A. B. da; Faria, SergioState-of-the art approaches towards stereo image coding exploit inter-view redundancy by employing block-matching methods for disparity estimation and compensation. However, the efficiency of these methods is affected by mismatched areas, due to occlusions, brightness variations, or perspective distortion between objects of the two views. In this paper we present a new prediction scheme for stereo image coding, that combines an implicit disparity estimation method, with an adaptive least squares (LS)-based filtering. The Multidimensional Multiscale Parser image coding algorithm was used to evaluate the efficiency of the proposed scheme. Experimental results demonstrate the advantage of LS prediction in stereo image coding. Furthermore, the rate-distortion performance of the MMP based stereo encoder is well above that of the state-of-the-art H.264/AVC Stereo Profile, especially at medium and high bit rates.
- Compression of touchless multiview fingerprintsPublication . Francisco, Nelson C.; Zaghetto, Alexandre; Macchiavello, Bruno; Silva, Eduardo A. B. da; Lima-Marques, Mamede; Rodrigues, Nuno M. M.; Faria, SergioRecently, touchless multiview fingerprinting technology has been proposed as an alternative to overcome the intrinsic problems of traditional contact-based systems. Nevertheless, compression of this kind of signal has not been fully evaluated and standardized. This paper investigates the comparative performance of several encoders for this data, namely WSQ, JPEG2000, H.264/AVC and MMP. Experimental results show that WSQ encoder, which is the current compression standard for contact-based fingerprints, is objectively outperformed by all others. In particular, MMP, which achieved the best results, outperforms WSQ by up to 4 dB.
- Computational complexity reduction methods for multiscale recurrent pattern algorithmsPublication . Francisco, Nelson C.; M. M. Rodrigues, Nuno; Silva, Eduardo A. B. da; Carvalho, Murilo B. de; Faria, SergioThe Multidimensional Multiscale Parser algorithm was originally proposed as a generic lossy data compression algorithm. An high degree of adaptivity and versatility allowed it to outperform state-of-the-art transform-based compression methods for a wide range of applications, from still images, compound documents, or even ECG's, just to name a few. However, as other pattern matching algorithms, it presents a high computational complexity. In this paper, we investigated several techniques that allowed to considerably reduce both the encoder's and the decoder's computational complexity, with marginal R-D performance losses. The most important reduction was achieved on the decoder, that reduced up to 95% the time required by the previous method. These improvements contribute to affirm MMP as an alternative to traditional transform-based encoders, approaching its computational complexity with that of transform-based algorithms.
- Efficient depth map coding using linear residue approximation and a flexible prediction frameworkPublication . Lucas, Luis F. R.; Rodrigues, Nuno M. M.; Pagliari, Carla L.; Silva, Eduardo A. B. da; Faria, Sérgio M. M. deThe importance to develop more efficient 3D and multiview data representation algorithms results from the recent market growth for 3D video equipments and associated services. One of the most investigated formats is video+depth which uses depth image based rendering (DIBR) to combine the information of texture and depth, in order to create an arbitrary number of views in the decoder. Such approach requires that depth information must be accurately encoded. However, methods usually employed to encode texture do not seem to be suitable for depth map coding. In this paper we propose a novel depth map coding algorithm based on the assumption that depth images are piecewise-linear smooth signals. This algorithm is designed to encode sharp edges using a flexible dyadic block segmentation and hierarchical intra-prediction framework. The residual signal from this operation is aggregated into blocks which are approximated using linear modeling functions. Furthermore, the proposed algorithm uses a dictionary that increases the coding efficiency for previously used approximations. Experimental results for depth map coding show that synthesized views using the depth maps encoded by the proposed algorithm present higher PSNR than their counterparts, demonstrating the method’s efficiency.
- 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
- 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.
- Intra Predictive Depth Map Coding Using Flexible Block PartitioningPublication . Lucas, Luis F. R.; Wegner, Krzysztof; M. M. Rodrigues, Nuno; Pagliari, Carla L.; Silva, Eduardo A. B. da; Faria, SergioA 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.
- Intra-prediction for color image coding using YUV correlationPublication . Lucas, Luís F.R.; Rodrigues, Nuno M. M.; Faria, Sérgio M. M. de; Silva, Eduardo A. B. da; Carvalho, Murilo B. de; Silva, Vitor M. M. daIn this paper we present a new algorithm for chroma prediction in YUV images, based on inter component correlation. Despite the YUV color space transformation for inter component decorrelation, some dependency still exists between the Y, U and V chroma components. This dependency has been previously used to predict the chrominance data from the reconstructed luminance. In this paper we show that a chrominance component can be more efficiently predicted by using the reconstructed data from both the luminance and the remaining chrominance signal. The proposed chroma prediction is implemented and tested using the Multidimensional Multiscale Parser (MMP) image encoding algorithm. It is shown that the new color prediction mode outperforms the originally proposed prediction methods. Furthermore, by using the new color prediction scheme, MMP is consistently better than the state-of-the-art H.264/AVC for coding both for the luminance and the chrominance image components.
- Light Field Disparity Map Enhancement with Morphological FilteringPublication . Lourenco, Rui; Thomaz, Lucas A.; Silva, Eduardo A. B. da; Assuncao, Pedro A. A.; Tavora, Luis M. N.; Faria, Sergio M. M. deLight field disparity estimation algorithms are comprised of two steps: an initial estimation step and a global optimization step. The initial estimation is often noisy and may contain high amplitude artefacts. Global optimization techniques might inadequately propagate these artefacts, providing suboptimal results. In this paper, an iterative morphological filter is proposed as an intermediate step or replacement to global optimization techniques. This algorithm iteratively filters the disparity map with an average of Open followed by Close and Close followed by Open morphological operations, enabling the removal of artefacts and noise, without adversely affecting the structure of the disparity map. The iterative open-close close-open filter attenuates the effect of artefacts and noise from an initial disparity estimation, achieving improvements of up to 90%, and more than 30%, on average, in terms of mean square error, when applied to the a structure-tensor-based initial estimation. In addition, the proposed method proves to be competitive with another state of the art algorithm, in terms of mean square error, and superior in terms of percentage of bad pixels.
- Multiscale recurrent pattern matching approach for depth map codingPublication . Graziosi, Danillo B.; Rodrigues, Nuno M. M.; Pagliari, Carla L.; Silva, Eduardo A. B. da; Faria, Sérgio M. M. de; Perez, Marcelo M.; Carvalho, Murilo B. deIn this article we propose to compress depth maps using a coding scheme based on multiscale recurrent pattern matching and evaluate its impact on depth image based rendering (DIBR). Depth maps are usually converted into gray scale images and compressed like a conventional luminance signal. However, using traditional transform-based encoders to compress depth maps may result in undesired artifacts at sharp edges due to the quantization of high frequency coefficients. The Multidimensional Multiscale Parser (MMP) is a pattern matching-based encoder, that is able to preserve and efficiently encode high frequency patterns, such as edge information. This ability is critical for encoding depth map images. Experimental results for encoding depth maps show that MMP is much more efficient in a rate-distortion sense than standard image compression techniques such as JPEG2000 or H.264/AVC. In addition, the depth maps compressed with MMP generate reconstructed views with a higher quality than all other tested compression algorithms.