Browsing by Author "Nunes, Paulo J. L."
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- Light Field Image Coding Based on Hybrid Data RepresentationPublication . Monteiro, Ricardo J. S.; Rodrigues, Nuno M. M.; Faria, Sérgio M.M.; Nunes, Paulo J. L.This paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited, as is demonstrated. This novel hybrid data representation approach allows to simultaneously exploit four types of redundancies: i) sub-aperture image intra spatial redundancy, ii) sub-aperture image inter-view redundancy, iii) intra-micro-image redundancy, and iv) inter-micro-image redundancy between neighboring micro-images. The proposed light field coding solution allows flexibility for several types of baselines, by adaptively exploiting the most predominant type of redundancy on a coding block basis. To demonstrate the efficiency of using a hybrid representation, this paper proposes a set of efficient pixel prediction methods combined with a pseudo-video sequence coding approach, based on the HEVC standard. Experimental results show consistent average bitrate savings when the proposed codec is compared to relevant state-ofthe-art benchmarks. For lenslet light field content, the proposed coding algorithm outperforms the HEVCbased pseudo-video sequence coding benchmark by an average bitrate savings of 23%. It is shown for the same light field content that the proposed solution outperforms JPEG Pleno verification models MuLE and WaSP, as these codecs are only able to achieve 11% and −14% bitrate savings over the same HEVC-based benchmark, respectively. The performance of the proposed coding approach is also validated for light fields with wider baselines, captured with high-density camera arrays, being able to outperform both the HEVCbased benchmark, as well as MuLE and WaSP.
- Light Field Image Coding using High Order Prediction TrainingPublication . Monteiro, Ricardo J. S.; Nunes, Paulo J. L.; Faria, Sergio; M. M. Rodrigues, NunoThis paper proposes a new method for light field image coding relying on a high order prediction mode based on a training algorithm. The proposed approach is applied as an Intra prediction method based on a two-stage block-wise high order prediction model that supports geometric transformations up to eight degrees of freedom. Light field images comprise an array of micro-images that are related by complex perspective deformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low order translational prediction models. The proposed prediction mode is able to exploit the non-local spatial redundancy introduced by light field image structure and a training algorithm is applied on different micro-images that are available in the reference region aiming at reducing the amount of signaling data sent to the receiver. The training direction that generates the most efficient geometric transformation for the current block is determined in the encoder side and signaled to the decoder using an index. The decoder is therefore able to repeat the high order prediction training to generate the desired geometric transformation. Experimental results show bitrate savings up to 12.57% and 50.03% relatively to a light field image coding solution based on low order prediction without training and HEVC, respectively.
- 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.
- Light field image coding with flexible viewpoint scalability and random accessPublication . Monteiro, Ricardo J. S.; Rodrigues, Nuno M. M.; Faria, Sérgio M. M.; Nunes, Paulo J. L.This paper proposes a novel light field image compression approach with viewpoint scalability and random access functionalities. Although current state-of-the-art image coding algorithms for light fields already achieve high compression ratios, there is a lack of support for such functionalities, which are important for ensuring compatibility with different displays/capturing devices, enhanced user interaction and low decoding delay. The proposed solution enables various encoding profiles with different flexible viewpoint scalability and random access capabilities, depending on the application scenario. When compared to other state-of-the-art methods, the proposed approach consistently presents higher bitrate savings (44% on average), namely when compared to pseudo-video sequence coding approach based on HEVC. Moreover, the proposed scalable codec also outperforms MuLE and WaSP verification models, achieving average bitrate saving gains of 37% and 47%, respectively. The various flexible encoding profiles proposed add fine control to the image prediction dependencies, which allow to exploit the tradeoff between coding efficiency and the viewpoint random access, consequently, decreasing the maximum random access penalties that range from 0.60 to 0.15, for lenslet and HDCA light fields.