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Your search keyword '"Assuncao, Pedro A."' showing total 114 results
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114 results on '"Assuncao, Pedro A."'

6. Lossless Coding of Light Fields Based on 4D Minimum Rate Predictors.

Author

Santos, Joao M., Thomaz, Lucas A., Assuncao, Pedro A. Amado, Cruz, Luis A. da Silva, Tavora, Luis, and de Faria, Sergio M. M.

Subjects
MATERIAL requirements planning, LOSSLESS data compression, DATA structures
Abstract

Common representations of light fields use four-dimensional data structures, where a given pixel is closely related not only to its spatial neighbours within the same view, but also to its angular neighbours, co-located in adjacent views. Such structure presents increased redundancy between pixels, when compared with regular single-view images. Then, these redundancies are exploited to obtain compressed representations of the light field, using prediction algorithms specifically tailored to estimate pixel values based on both spatial and angular references. This paper proposes new encoding schemes which take advantage of the four-dimensional light field data structures to improve the coding performance of Minimum Rate Predictors. The proposed methods expand previous research on lossless coding beyond the current state-of-the-art. The experimental results, obtained using both traditional datasets and others more challenging, show bit-rate savings no smaller than 10%, when compared with existing methods for lossless light field compression. [ABSTRACT FROM AUTHOR]

Published
2022
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20. Accurate Segmentation of Dermoscopic Images based on Local Binary Pattern Clustering

Author

A A Assuncao Pedro, Rui Pedro Paiva, M M Pereira Pedro, M N Tavora Luis, M M de Faria Sergio, and Rui Fonseca-Pinto

Subjects
010302 applied physics, Computer science, business.industry, Local binary patterns, Image processing, Pattern recognition, 02 engineering and technology, 01 natural sciences, Accurate segmentation, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Medical imaging, 020201 artificial intelligence & image processing, Segmentation, Artificial intelligence, Border line, Skin lesion, business, Cluster analysis
Abstract

Segmentation 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.

Published
2019

23. Light Field Image Dataset of Skin Lesions

Author

de Faria, Sergio M. M., primary, Henrique, Martinha, additional, Filipe, Jose N., additional, Pereira, Pedro M. M., additional, Tavora, Luis M. N., additional, Assuncao, Pedro A. A., additional, Santos, Miguel O., additional, Fonseca-Pinto, Rui, additional, Santiago, Felicidade, additional, and Dominguez, Victoria, additional

Published
2019
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36. Error Concealment-Aware Encoding for Robust Video Transmission.

Author

Carreira, Joao F. M., Ekmekcioglu, Erhan, Kondoz, Ahmet, Assuncao, Pedro A., and de Faria, Sergio M. M.

Subjects
STREAMING video & television, ENCODING, DATA transmission systems, ROBUST control, VIDEO coding, STREAMING technology
Abstract

In this paper an error concealment (EC)-aware encoding scheme is proposed to improve the quality of decoded video in broadcast environments subject to transmission errors and data loss. The proposed scheme is based on a scalable coding approach where the best EC methods to be used at the decoder are optimally determined at the encoder and signalled to the decoder through supplemental enhancement information messages. Such optimal EC modes are found by simulating transmission losses, followed by a Lagrangian optimization of the signalling rate—EC distortion cost. A generalized saliency-weighted distortion is used and the residue between coded frames and their EC substitutes is encoded using a rate-controlled enhancement layer. When data loss occurs the signalling information is used by the decoder to improve the reconstruction quality. The simulation results show that the proposed method achieves consistent quality gains in comparison with other reference methods and previous works. Using only the EC mode signalling, i.e., without any residue transmitted in the enhancement layer, an average PSNR gain up to 2.95 dB is achieved, while using the full EC-aware scheme, i.e., including residue encoded in the enhancement layer, the proposed scheme outperforms other comparable methods, with a PSNR gain up to 3.79 dB. [ABSTRACT FROM AUTHOR]

Published
2019
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39. Plenary session 1: Engineering leadership & cognitive computing

Author

Timotheou, Nicos M., primary, Reumann, Matthias, additional, Milanovic, Jovica V., additional, Kornegay, L. Gene, additional, Stubner, Ralph, additional, Hernandez-Castro, Julio, additional, Amado Assuncao, Pedro A., additional, Georgiou, Julius, additional, and Riede, Moritz, additional

Published
2016
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41. A Two-Stage Approach for Robust HEVC Coding and Streaming.

Author

Carreira, Joao F. M., Assuncao, Pedro A., de Faria, Sergio M. M., Ekmekcioglu, Erhan, and Kondoz, Ahmet

Subjects
*STREAMING video & television, *VIDEO coding, *COMPUTER algorithms, *MATHEMATICAL optimization, *ROBUST control
Abstract

The increased compression ratios achieved by the High Efficiency Video Coding (HEVC) standard lead to reduced robustness of coded streams, with increased susceptibility to network errors and consequent video quality degradation. This paper proposes a method based on a two-stage approach to improve the error robustness of HEVC streaming, by reducing temporal error propagation in the case of frame loss. The prediction mismatch that occurs at the decoder after frame loss is reduced through the following two stages. First, at the encoding stage, the reference pictures are dynamically selected based on constraining conditions and Lagrangian optimization, which distributes the use of reference pictures, by reducing the number of prediction units that depend on a single reference. Second, at the streaming stage, a motion vector (MV) prioritization algorithm, based on spatial dependencies, selects an optimal subset of MVs to be transmitted, redundantly, as side information to reduce mismatched MV predictions at the decoder. The simulation results show that the proposed method significantly reduces the effect of temporal error propagation. Compared with the reference HEVC, the proposed reference picture selection method is able to improve the video quality at low-packet-loss rates (e.g., 1%) using the same bitrate, achieving quality gains up to 2.3 dB for 10% of packet loss ratio. It is shown, for instance, that the redundant MVs are able to boost the performance achieving quality gains of 3 dB when compared with the reference HEVC, at the cost using 4% increase in total bitrate. [ABSTRACT FROM AUTHOR]

Published
2018
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