Browsing by Author "Faria, Sergio M. M. de"
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- 4D Light Field Disparity Map estimation using Krawtchouk PolynomialsPublication . Lourenco, Rui; Rivero-Castillo, Daniel; Thomaz, Lucas A.; Assuncao, Pedro A. A.; Tavora, Luis M. N.; Faria, Sergio M. M. deThis work presents an improved method to estimate disparity maps obtained from light field cameras using a novel edge detection algorithm based on Krawtchouk polynomials. The proposed method takes advantage of these polynomials to determine gradient information and find the edges based on automatically estimated weak and strong thresholds. The calculated edges in the gray scale epipolar plane image representation of a light field are then used to improve the accuracy of object boundaries in the the disparity map. The proposed method achieves better results when compared to other edge detection algorithms, both in terms of objective and subjective quality, specifically by reducing the mean squared error and the artifacts in the object boundaries. Furthermore, on average, the proposed method outperforms the state-of-the-art depth estimation algorithms, in terms of the objective quality of the final disparity map, namely for the commonly used HCI dataset.
- Compression of medical images using MRP with bi-directional prediction and histogram packingPublication . Santos, Joao M.; Guarda, Andre F.R.; Cruz, Luís A. da Silva; Rodrigues, Nuno M. M.; Faria, Sergio M. M. deMedical imaging technology has become essential for the improvement of medical practice. This led to advances in the technology, namely in image sampling resolutions, pixel bit-depth and inter slice resolution. Additionally, common use of medical images, the life expectancy of patients and legal restrictions led to increasing storage costs. Therefore, efficient compression of medical image data is in high demand, for archiving and transmission. In this work we propose to improve the compression efficiency of the Minimum Rate Predictors lossless encoder, by adding bi-directional prediction support and a histogram packing technique. The results show that the proposed method presents a higher compression efficiency than state-of-the-art HEVC encoder. The compression efficiency is improved by 20%, on average, when compared to HEVC and by 46.1% when compared with the original MRP algorithm.
- Disparity compensation of light fields for improved efficiency in 4D transform-based encodersPublication . Santos, Joao M.; Thomaz, Lucas A.; Assuncao, Pedro A. A.; Cruz, Luis A. da Silva; Tavora, Luis M. N.; Faria, Sergio M. M. deEfficient light field en coders take advantage of the inherent 4D data structures to achieve high compression performance. This is accomplished by exploiting the redundancy of co-located pixels in different sub-aperture images (SAIs) through prediction and/or transform schemes to find a m ore compact representation of the signal. However, in image regions with higher disparity between SAIs, such scheme's performance tends to decrease, thus reducing the compression efficiency. This paper introduces a reversible pre-processing algorithm for disparity compensation that operates on the SAI domain of light field data. The proposed method contributes to improve the transform efficiency of the encoder, since the disparity-compensated data presents higher correlation between co-located image blocks. The experimental results show significant improvements in the compression performance of 4D light fields, achieving Bjontegaard delta rate gains of about 44% on average for MuLE codec using the 4D discrete cosine transform, when encoding High Density Camera Arrays (HDCA) light field images.
- Lossless Compression of Medical Images Using 3-D PredictorsPublication . Lucas, Luis F. R.; M. M. Rodrigues, Nuno; Cruz, Luis A. da Silva; Faria, Sergio M. M. deThispaper describes a highly efficientmethod for lossless compression of volumetric sets of medical images, such as CTs or MRIs. The proposed method, referred to as 3-D-MRP, is based on the principle ofminimum rate predictors (MRPs), which is one of the state-of-the-art lossless compression technologies presented in the data compression literature. The main features of the proposed method include the use of 3-D predictors, 3-D-block octree partitioning and classification, volume-based optimization, and support for 16-b-depth images. Experimental results demonstrate the efficiency of the 3-D-MRP algorithm for the compression of volumetric sets of medical images, achieving gains above 15% and 12% for 8- and 16-bitdepth contents, respectively, when compared with JPEGLS, JPEG2000, CALIC, and HEVC, aswell as other proposals based on the MRP algorithm.
- Optimizing GPU Code for CPU Execution Using OpenCL and Vectorization: A Case Study on Image CodingPublication . Pereira, Pedro M. M.; Domingues, Patrício; M. M. Rodrigues, Nuno; Gabriel Falcao; Faria, Sergio M. M. deAlthough OpenCL aims to achieve portability at the code level, di erent hardware platforms requires di erent approaches in order to extract the best performance for OpenCL-based code. In this work, we use an image encoder originally tuned for OpenCL on GPU (OpenCL-GPU), and optimize it for multi-CPU based platforms. We produce two OpenCL-based versions: i) a regular one (OpenCL-CPU) and ii) a CPU vector-based one (OpenCL-CPU-Vect). The use of CPU vectorization exploits the OpenCL support, making it much simpler than directly coding with SIMD instructions such as SSE and AVX. Globally, while the OpenCL-GPU version is the fastest when run on a high end GPU requiring around 580 seconds to encode the Lenna image, its performance drops roughly 65% when run unchanged on a multicore CPU machine. For the CPU tuned versions, OpenCL-CPU encodes the Lenna image in 805 seconds, while the vectorization-based approach executes the same operation in 672 seconds. Results show that meaningful performance gains can be achieved by tailoring the OpenCL code to the CPU, and that the use of CPU vectorization instructions through OpenCL is both rather simple and performance rewarding.
- Scalable Coding of 360-degree Video for Streaming Adaptation at 5G Network EdgesPublication . Carreira, J.; Faria, Sergio M. M. de; Tavora, Luis M. N.; Navarro, Antonio; Assuncao, Pedro A. A.The huge amount of data that is necessary to capture the full field-of-view (FoV) in omnidirectional video, i.e., 360°, imposes the use of highly efficient compressed formats as well as adaptive broadcast and streaming mechanisms, such as those foreseen for 5G networks. To cope with the demanding requirements of 360° video streaming over 5G networks, this work proposes a scalable 360° video coding architecture, by enabling adaptation through the Multi-Access Edge Computing (MEC) server in two different domains of the spherical visual content, namely spatial resolution and FoV. In the proposed architecture two-layers are encoded from the input 360° video content: (i) the base-layer (BL), encoding each 360° image as a whole, at a lower spatial resolution; (ii) the enhancement-layer (EL) encoding each spherical image as a set of multiple FoVs with higher spatial resolution. Such arrangement enables flexible stream adaptation for the smart decision algorithms to be implemented at the MEC server, enabling significant reduction of the overall bit rate through the radio interface. The simulation results show that the proposed scalable coding scheme allows a great deal of bit rate savings across the 5G network, achieving 36% of bit rate saving, on average, for a 90° FoV in comparison with conventional single-layer coding.
- Sparse least-squares prediction for intra image codingPublication . Lucas, Luis F. R.; M. M. Rodrigues, Nuno; Pagliari, Carla L.; Silva, Eduardo A. B. da; Faria, Sergio M. M. deThis paper presents a new intra prediction method for efficient image coding, based on linear prediction and sparse representation concepts, denominated sparse least-squares prediction (SLSP). The proposed method uses a low order linear approximation model which may be built inside a predefined large causal region. The high flexibility of the SLSP filter context allows the inclusion of more significant image features into the model for better prediction results. Experiments using an implementation of the proposed method in the state-of-the-art H.265/HEVC algorithm have shown that SLSP is able to improve the coding performance, specially in the presence of complex textures, achieving higher coding gains than other existing intra linear prediction methods. © 2015 IEEE.
- Spatial error concealment for intra-coded depth maps in multiview video-plus-depthPublication . Assunção, Pedro; Marcelino, Sylvain; Soares, Salviano; Faria, Sergio M. M. deTransmission errors or packet loss in depth maps have great impact on the decoding quality and view synthesis of 3D and multiview video. Thus efficient methods to recover corrupted depth data are critical functions for accurate view rendering. This paper pro poses an error concealment method for intra-coded depth maps, based on spatial intra and inter-view methods, which exploit neighbouring data of depth and colour images received error-free. A novel three-stage processing algorithm is devised to reconstruct sharp depth transitions (i.e. lost depth contours), using a disparity map and geometric interpolation based on parametric Bezier curves. The simulation results obtained from different views of various MVD sequences, for different packetisation modes and a wide range of packet loss rates (PLR), show that the proposed method consistently leads to quality improvement of synthesised images in comparison with reference methods.
- Versatile Video Coding Of 360° Video Using Adaptive Resolution ChangePublication . Carreira, J.; Faria, Sergio M. M. de; Tavora, Luis M. N.; Navarro, Antonio; Assuncao, Pedro A. A.Encoding 360° video with ultra high spatial resolution requires high bitrates to guarantee acceptable QoE in video delivery services. However, since in general the full Field-of-View (FoV), i.e., 360°, is not required at once, a great deal of bandwidth can be saved if only a limited FoV is delivered, according to content relevancy or/and user demand. This work addresses this problem using the concept of Adaptive Resolution Change (ARC) defined in the forthcoming Versatile Video Coding (VVC) standard, by dynamically mapping the full FoV into multiple video frames with different spatial resolutions. Those FoVs attracting more visual attention are encoded with higher resolution while the others are encoded with lower resolution, thus without compromising the visual quality and resolution of the most relevant regions. The simulation results show that the proposed adaptive coding scheme is able to deliver high quality video for the most relevant FoV at any time instant, achieving a maximum bitrate reduction of 37.2%.