Showing papers by "Mohamed-Chaker Larabi published in 2016"

On the Efficiency of Image Metrics for Evaluating the Visual Quality of 3D Models

Abstract: 3D meshes are deployed in a wide range of application processes (e.g., transmission, compression, simplification, watermarking and so on) which inevitably introduce geometric distortions that may alter the visual quality of the rendered data. Hence, efficient model-based perceptual metrics, operating on the geometry of the meshes being compared, have been recently introduced to control and predict these visual artifacts. However, since the 3D models are ultimately visualized on 2D screens, it seems legitimate to use images of the models (i.e., snapshots from different viewpoints) to evaluate their visual fidelity. In this work we investigate the use of image metrics to assess the visual quality of 3D models. For this goal, we conduct a wide-ranging study involving several 2D metrics, rendering algorithms, lighting conditions and pooling algorithms, as well as several mean opinion score databases. The collected data allow (1) to determine the best set of parameters to use for this image-based quality assessment approach and (2) to compare this approach to the best performing model-based metrics and determine for which use-case they are respectively adapted. We conclude by exploring several applications that illustrate the benefits of image-based quality assessment.

Knowledge-based Taxonomic Scheme for Full-Reference Objective Image Quality Measurement Models

Abstract: In this paper, we propose a knowledge-based taxonomic scheme of the objective image quality assessment metrics including the key concepts involved for each approach. Our classification is constructed according to six criteria based on the information available at each stage of the design process. The novelty of the present classification scheme is that the six layers are linked via a single concept where each layer represents a single type of knowledge about: 1) the reference image, 2) the degradation type, 3) the visual perception field, 4) the human visual physiology and psychophysical mechanisms, 5) the processes of the visual information analysis, and finally 6) knowledge about perceptual image representation and coding. The first layer helps delineate boundaries between full-reference image quality assessment metrics, that are further classified trough layers 2 to 6, and other families (reduced-reference and no-reference). In addition, gradual degrees are considered for knowledge about specific areas related to visual quality evaluation processes. The proposed taxonomic framework is intended to be stepwise, to help sorting out the fundamental ideas behind the development of objective image quality metrics often working on the luminance channel or marginally on the RGB channels. The aim is to congregate the already published classification schemes and to methodologically expand new aspects according to which an efficient and straightforward classification of the image quality assessment algorithms becomes possible. This is significant because of the increasing number of developed metrics. Furthermore, a systematic summarisation is necessary in order to facilitate the search and application of image quality techniques.

On the performance of 3D just noticeable difference models

Abstract: The just noticeable difference (JND) notion reflects the maximum tolerable distortion. It has been extensively used for the optimization of 2D applications. For stereoscopic 3D (S3D) content, this notion is different since it relies on different mechanisms linked to our binocular vision. Unlike 2D, 3D-JND models appeared recently and the related literature is rather limited. These models can be used for the sake of compression and quality assessment improvement for S3D content. In this paper, we propose a deep and comparative study of the existing 3D-JND models. Additionally, in order to analyze their performance, the 3D-JND models have been integrated in recent metric dedicated to stereoscopic image quality assessment (SIQA). The results are reported on two widely used S3D image databases.

A reduced reference video quality assessment of H.264 and mpeg2 codec based on sharpness metric

Abstract: In this paper, we propose a new perceptually significant video quality metric for the H.264/Motion Picture Expert Group (MPEG)-4 Advanced Video Coding (AVC) and MPEG2 standard. Ourmethod operates in the spatial domain by using the Sobel filter. The proposed approach does notrequire a high computational complexity and can be suitable for real-time evaluation. We evaluatethe performance of the proposed method by using three Common Intermediate Format sequences at dif-ferent compression rates. The comparison of the obtained results is made with some video qualitymodels using “LIVE”, “IVP” and “IRCCyN/IVC 1080i” databases. The performance metrics, i.e. Pearson and Spearman correlation coefficients, indicate that the proposed method gives a good performance inH264 and MPEG2 codec distortions with the three databases comparing with other models.

Heuristic inspired search method for fast wedgelet pattern decision

Abstract: The 3D High Efficiency Video Coding (3D-HEVC) is the latest 3D extension of the HEVC video coding standard. It supports multi-view videos plus depth (MVD), which is a sophisticated format for enhanced 3D content. Depth modelling modes (DMM) are adopted in the 3D-HEVC for better sharp edge encoding. However, employing DMM causes important computational complexity. In this paper, we propose a new method for fast wedgelet pattern decision in 3D-HEVC. In order to avoid unnecessary evaluation of the DMMs, a new early termination based on the smoothness of the current block is adopted. Besides, based on the shuffled frog leaping algorithm, a new heuristic method to search the optimal wedgelet pattern for DMM1 Depth mode is introduced. The proposed algorithm outperforms the HTM16.0 implemented scheme in terms of encoding time with similar coding efficiency.

Heuristic inspired search method for fast wedgelet pattern decision in 3D-HEVC

Abstract: The 3D High Efficiency Video Coding (3D-HEVC) is the latest 3D extension of the HEVC video coding standard. It supports multi-view videos plus depth (MVD), which is a sophisticated format for enhanced 3D content. Depth modeling modes (DMM) are adopted in the 3D-HEVC for better sharp edge encoding. However, employing DMM causes important computational complexity. In this paper, we propose a new method for fast wedgelet pattern decision in 3D-HEVC. In order to avoid unnecessary evaluation of the DMMs, a new early termination based on the smoothness of the current block is adopted. Besides, based on the shuffled frog leaping algorithm, a new heuristic method to search the optimal wedgelet pattern for DMM1 Depth mode is introduced. The proposed algorithm outperforms the HTM16.0 implemented scheme in terms of encoding time with similar coding efficiency.

A no reference quality metric to measure the blocking artefacts for video sequences

Abstract: The need to measure video quality arises in the development of video equipment and in the delivery and storage of video and image information. In this paper, we propose a new perceptually significant video quality metric to estimate the effect of block coding for standards H.264 AVC and MPEG2. Our method operates in the spatial domain and does not require a high complexity of computation. We evaluate the performance of the proposed method by using three sequences CIF ‘common intermediate file’ with different compression rate. We compare it with Suthaharan’s and MSU’s techniques by using ‘LIVE’ and ‘IVP’ databases. Results indicate that the proposed method outperforms Suthaharan’s and MSU techniques in H264 coder. They also indicate that our method is more effective than MSU’s and Suthaharan’s techniques for the H.264 AVC standards with the Spearman Rank Order Correlation Coefficient.

Universal blind image quality assessment for stereoscopic images

Abstract: Quality assessment of stereoscopic 3D images is a challenging field and represents a key factor in the success of 3D multimedia applications. Despite the important research effort in the last few years, there is no commonly accepted metric ensuring a reliable 3D quality evaluation. This statement becomes even worse when it comes to asymmetrically distorted stereoscopic content. In this paper, we propose a universal blind quality assessment metric for stereoscopic images relying on: 1) distortion type detection and 2) asymmetry nature determination. Based of the latter key information, the 3D image quality is appropriately estimated using a binocular combination strategy. Experimental results showed that the proposed metric reached a significant prediction consistency and accuracy when compared with state-of-the-art metrics.

On the selection of residual formula for HDR video coding

Abstract: High Dynamic Range (HDR) videos are commonly compressed using existing Low Dynamic Range (LDR) coding standards. This necessarily implies a Tone Mapping (TM) stage which aims at reducing the input video range while preserving the most significant scene details. In most cases, a residual sequence is encoded and used at the decoder side to recover the HDR content. The challenge is to efficiently encode both LDR sequences (TM and residual) without compromising the quality of the reconstructed video. Furthermore, the choice of the residual sequence can have an important impact on the HDR video coder performances. In this work, we aim to study and analyse different approaches for residual determination. The performance is discussed in terms of entropy of the residual and video coding. Objective assessments show that differential residual presents much higher efficiency than ratio residuals in terms of bandwidth saving and HDR reconstruction quality.

Adaptive colorization-based compression for stereoscopic images

Abstract: Considerable research efforts have been devoted to stereo image compression. However, most of them focused on the luminance and ignored the chromatic information. Consequently, in this paper we propose a stereo color image coding method based on colorization. The main idea is to compress one view of the stereo pair using a standard coding method, while for the other view, only the luminance component is considered for compression. The chromatic information of this latter view are transmitted to the decoder for a few representative pixels (RPs) only. These RPs are defined using a novel proposed RP extraction method based on skeletonization. At decoder side, color values of all the remaining pixels are reconstructed by colorization methods. Experimental results showed that our coding method can achieve considerable bit-rate saving compared to conventional coding method.

Color Management in HDR Imaging

Abstract: A large volume of research exists that addresses the mapping, compression, expansion, and other types of manipulation of the extended luminance range afforded by high dynamic range technologies. However, most of this research focuses exclusively on the luminance dimension, ignoring the chromatic information in images. This is particularly problematic given the parallel push toward extending not only the luminance range but also the chromatic range. In this chapter, we look at solutions that combine the ideas of high dynamic range imaging with color management approaches in different contexts.

Perceptually-adaptive quantization for stereoscopic video coding

Abstract: In this paper, we present a novel perceptually-based optimization for the improvement of stereoscopic video coding efficiency. The main idea of this proposed scheme is to adaptively adjust the quantization parameter by taking into account the Human Visual System perceptual characteristics. For this, a saliency map is generated from both views and then segmented into salient and non-salient regions. To make the proposed scheme effective, and inspired from the binocular suppression theory, the asymmetry is ensured by altering the saliency map and not the view. As a result, the proposed perceptual coding scheme effectively reduces the bit-budget without affecting the perceptual quality based on an optimization approach with asymmetric video coding taking into account the saliency map of each view. Experimental results on HEVC-MV show that the proposed algorithm can achieve over 20% bit-rate saving while preserving the perceived image quality.