Browsing by Author "Lucas, Luis F. R."
Now showing 1 - 5 of 5
Results Per Page
Sort Options
- 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.
- 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.
- 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.
- 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.
- 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.