Percorrer por autor "Faria, Sérgio M. M. de"
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- Accurate Segmentation of Dermoscopic Images based on Local Binary Pattern ClusteringPublication . Pereira, Pedro M. M.; Fonseca-Pinto, Rui; Paiva, Rui Pedro; Tavora, Luis M. N.; Assunção, Pedro A. A.; Faria, Sérgio M. M. deSegmentation is a key stage in dermoscopic image processing, where the accuracy of the border line that defines skin lesions is of utmost importance for subsequent algorithms (e.g., classification) and computer-aided early diagnosis of serious medical conditions. This paper proposes a novel segmentation method based on Local Binary Patterns (LBP), where LBP and K-Means clustering are combined to achieve a detailed delineation in dermoscopic images. In comparison with usual dermatologist-like segmentation (i.e., the available ground-truth), the proposed method is capable of finding more realistic borders of skin lesions, i.e., with much more detail. The results also exhibit reduced variability amongst different performance measures and they are consistent across different images. The proposed method can be applied for cell-based like segmentation adapted to the lesion border growing specificities. Hence, the method is suitable to follow the growth dynamics associated with the lesion border geometry in skin melanocytic images.
- Efficient depth error concealment for 3D video over error-prone channelsPublication . Marcelino, S.; Assunção, P.; Faria, Sérgio M. M. de; Soares, S.This paper addresses the problem of multivew videoplus-depth (MVD) decoding with corrupted depth maps due to transmission errors. A method for spatial error concealment of depth maps in MVD is proposed to efficiently recover lost blocks. The proposed method relies on the colour image and geometric curve fitting for accurate reconstruction of the lost contour segments in the corresponding depth map areas. Such reconstructed depth map contours are then used as boundaries at different depth planes to recover the missing depth values through weighted interpolation. The method performance is evaluated by the objective quality (PSNR) of the synthesised views. Images decoded with the reconstructed depth maps are compared with those of a reference method based on bidirectional interpolation. The proposed method exhibits PSNR gains up to 1.66dB higher than the reference one and better performance is consistently achieved for different visual content.
- 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.
- Efficient Recurrent Pattern Matching Video CodingPublication . Francisco, Nelson C.; Rodrigues, Nuno M. M.; B. da Silva, Eduardo A.; Bresciani de Carvalho, Murilo; Faria, Sérgio M. M. deIn this paper, we propose a pattern-matchingbased algorithm for video compression. This algorithm, named multidimensional multiscale parser (MMP)-Video, is based on the H.264/AVC video encoder, but uses a pattern-matching paradigm instead of the state-of-the-art transform-quantizationentropy encoding approach. The proposed method adopts the use of multiscale recurrent patterns to compress both spatial and temporal prediction residues, totally replacing the use of transforms and quantization. Experimental results show that the coding performance of MMP-Video is better than the one of H.264/AVC high profile, especially for medium to high bit-rates. The gains range up to 0.7 dB, showing that, in spite of its larger computational complexity, the use of multiscale recurrent pattern matching paradigm deserves being investigated as an alternative for video compression.
- Evaluation of Focus Metrics in Extended Depth-of-field ReconstructionPublication . Filipe, Jose N.; Távora, Luis M.N.; Assunção, Pedro A. A.; Fonseca-Pinto, Rui; Faria, Sérgio M. M. deThe performance of focus metrics in the evaluation of refocused images from light fields is investigated in this paper. To this aim, the paper presents a comprehensive study on the performance of a large set of different focus metrics (34 in total) in the evaluation of patch-based extended depth-of-field reconstructed images (e.g., all-in-focus). The new findings of this work demonstrate that optimal reconstruction of extended depth-of-field images, from light fields captured with focused plenoptic cameras, is not consistent with the focus level figures computed by available focus metrics. The results show that a higher focus level, as given by such computational methods, does not actually correspond to better all-in-focus images, thus indicating that currently available focus metrics are not suitable for evaluating the quality of extended depth-of-field reconstruction. The results obtained through subjective evaluation confirm that objective focus metrics fail to indicate the best focused images. Finally, the paper presents recommendations to adapt existing metrics to extended depth-of-field reconstruction in plenoptic imaging.
- 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.
- Integer DCT Approximation With Arbitrary Size and Adjustable PrecisionPublication . Thomaz, Lucas A.; Assunção, Pedro A. A.; Tavora, Luis M. N.; Faria, Sérgio M. M. deThis letter proposes a method to obtain integer reversible discrete cosine transforms for generic transform-based coding schemes. The novelty of the proposed method, which is based on decomposition of the DCT-II matrix into two triangular and one diagonal matrices, is twofold: (i) the new matrices can be of arbitrary size, i.e., any square N\times N dimension, thus suitable for applications where non power-of-2 dimensions are required; (ii) they can be designed with adjustable precision in a trade-off with the number of representation bits. Furthermore, improvements are also proposed over the base scheme to avoid numerical issues when working with large matrices and to obtain more reliable approximations. The performance evaluation demonstrate the effectiveness of the proposed transforms to approximate the coding gain capabilities of the original DCT-II.
- 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 image Coding using high-order intrablock predictionPublication . Monteiro, Ricardo J. S.; Nunes, Paulo J. L.; Rodrigues, Nuno M. M.; Faria, Sérgio M. M. deThis paper proposes a two-stage high-order intrablock prediction method for light field image coding. This method exploits the spatial redundancy in lenslet light field images by predicting each image block, through a geometric transformation applied to a region of the causal encoded area. Light field images comprise an array of microimages that are related by complex geometric transformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low-order translational prediction models. The two-stage nature of the proposed method allows us to choose the order of the prediction model most suitable for each block, ranging from pure translations to projective or bilinear transformations, optimized according to an appropriate rate-distortion criterion. The proposed higher order intrablock prediction approach was integrated into a high efficiency video coding (HEVC) codec and evaluated for both unfocused and focused light field camera models, using different resolutions and microlens arrays. Experimental results show consistent bitrate savings, which can go up to 12.62%, when compared to a lower order intrablock prediction solution and 49.82% when compared to HEVC still picture coding.
- A method to improve HEVC lossless coding of volumetric medical imagesPublication . F.R. Guarda, André F. R.; Santos, João M.; Cruz, Luís A. da Silva; Assunção, Pedro A. A.; Rodrigues, Nuno M. M.; Faria, Sérgio M. M. deMedical imaging technology and applications are continuously evolving, dealing with images of increasing spatial and temporal resolutions, which enable more accurate processing, feature analysis and medical diagnosis. However, the increase in resolution also requires a growing amount of data to be stored, processed and exchanged or transmitted through networks. Despite the high coding efficiency achieved by the most recent image and video coding standards in lossy compression, they are not well suited for quality-critical medical image compression where either near-lossless or lossless coding is required. In this paper we propose a method to improve lossless coding of volumetric medical images, such as Magnetic Resonance and Computed Tomography, and medical sequences such as X-ray Angiography images, using the latest standard High Efficiency Video Encoder (HEVC). New pixel-wise prediction techniques are proposed to extend the current HEVC lossless tools, based on Least-Squares Prediction (LSP). Experimental results show a bitrate reduction of over 44%, when compared to DICOM recommended encoders, and 13.8% when compared to standard lossless HEVC, for 8 bpp volumetric images, and over 8% and 4.6%, respectively, for volumetric images using more than 8 bpp.