This paper presents a reliable image and video secret storing method, aiming at ensuring the protected storage of multimedia files without risk for their owner to have their privacy violated. It relies on a particular property (standardized in MPEG-A Part.21 VIMAF) of video and image standards such as H.264/AVC, H.265/HEVC and MPEG-HEIF: a non negligible portion of the bitstream (so-called cipherable bits) can be altered without modifying the decodability of the stream. Such a modification results in an image or a video that is both a valid and visually encrypted media file. Not willing to be bothered by a complex key management system, we take inspiration from Shamir's secret sharing scheme, and propose a method where the secret to be shared is the original (unciphered) set of cipherable bits, that are encoded and divided in$n$shares, among which$k-1$or less do not permit to reconstruct the secret, while$k$or more allow to recover it. Those$n$shares are then used to generate$n$ciphered fully standard compliant versions of the media. The rightful owner of the file will easily store these$n$versions in various Cloud storage locations, and recover them all when the fully deciphered file will be needed, while a hacker will most generally obtain only some of those files, hence not be capable to decrypt the file.

VVC is the next generation video coding standard, offering coding capability beyond HEVC standard. The high computational complexity of the latest video coding standards requires high-level parallelism techniques, in order to achieve real-time and low latency encoding and decoding. HEVC and VVC include tile grid partitioning that allows to process simultaneously rectangular regions of a frame with independent threads. The tile grid may be further partitioned into a horizontal sub-grid of Rectangular Slices (RSs), increasing the partitioning flexibility. The dynamic Tile and Rectangular Slice (TRS) partitioning solution proposed in this paper benefits from this flexibility. The TRS partitioning is carried-out at the frame level, taking into account both spatial texture of the content and encoding times of previously encoded frames. The proposed solution searches the best partitioning configuration that minimizes the trade-off between multi-thread encoding time and encoding quality loss. Experiments prove that the proposed solution, compared to uniform TRS partitioning, significantly decreases multi-thread encoding time, with slightly better encoding quality.

Block partition structure is a critical module in video coding scheme to achieve significant gap of compression performance. Under the exploration of the future video coding standard, named Versatile Video Coding (VVC), a new Quad Tree Binary Tree (QTBT) block partition structure has been introduced. In addition to the QT block partitioning defined in High Efficiency Video Coding (HEVC) standard, new horizontal and vertical BT partitions are enabled, which drastically increases the encoding time compared to HEVC. In this paper, we propose a lightweight and tunable QTBT partitioning scheme based on a Machine Learning (ML) approach. The proposed solution uses Random Forest classifiers to determine for each coding block the most probable partition modes. To minimize the encoding loss induced by misclassification, risk intervals for classifier decisions are introduced in the proposed solution. By varying the size of risk intervals, tunable trade-off between encoding complexity reduction and coding loss is achieved. The proposed solution implemented in the JEM-7.0 software offers encoding complexity reductions ranging from 30average for only 0.7% to 3.0% Bjxntegaard Delta Rate (BDBR) increase in Random Access (RA) coding configuration, with very slight overhead induced by Random Forest. The proposed solution based on Random Forest classifiers is also efficient to reduce the complexity of the Multi-Type Tree (MTT) partitioning scheme under the VTM-5.0 software, with complexity reductions ranging from 25% to 61% in average for only 0.4% to 2.2% BD-BR increase.

Block partition structure is a critical module in video coding scheme to achieve significant gap of compression performance. Under the exploration of future video coding standard by the Joint Video Exploration Team (JVET), named Versatile Video Coding (VVC), a new Quad Tree Binary Tree (QTBT) block partition structure has been introduced. In addition to the QT block partitioning defined by High Efficiency Video Coding (HEVC) standard, new horizontal and vertical BT partitions are enabled, which drastically increases the encoding time compared to HEVC. In this paper, we propose a fast QTBT partitioning scheme based on a Machine Learning approach. Complementary to techniques proposed in literature to reduce the complexity of HEVC Quad Tree (QT) partitioning, the propose solution uses Random Forest classifiers to determine for each block which partition modes between QT and BT is more likely to be selected. Using uncertainty zones of classifier decisions, the proposed complexity reduction technique is able to reduce in average by 30% the encoding time of JEM-v7.0 software in Random Access configuration with only 0.57% Bjøntegaard Delta Rate (BD-BR) increase.

Transmission and compression technologies advancement over the past decade led to a shift of multimedia content towards cloud systems. Multiple copies of the same video are available through numerous distribution systems. Different compression levels, algorithms and resolutions are used to match the requirements of particular applications. As 4k display technologies are rapidly adopted, resolution enhancement algorithms are of vital importance. Current solutions do not take into account the particularities of different video encoders, while video reconstruction methods from compressed sources do not provide resolution enhancement. In this paper, we propose a multi source compressed video enhancement framework, where each description can have a different compression level and resolution. Using a variational formulation based on a modern proximal dual splitting algorithm, we efficiently combine multiple descriptions of the same video. Two applications are proposed: combining two compressed low resolution (LR) descriptions of a video sequence into a high resolution (HR) description and enhancing a compressed HR video using a LR compressed description. Tests are performed over multiple video sequences encoded with high efficiency video coding, at different compression levels and resolutions obtained through multiple down-sampling methods.

This paper proposes an extended selective encryption (SE) method for both H.264/advanced video coding (AVC) (CABAC) and High Efficiency Video Coding (HEVC) streams, addressing the main security issue that SE is facing: content protection, related to the amount of information leakage through a protected video. Our contribution is the improvement in the visual distortion induced by SE approaches. Previous works on both H.264/AVC (CABAC) and HEVC limit encryption to bins treated by one specific mode of CABAC-its bypass mode-which has the advantage of preserving the overall bitrate, we propose here to also rely on the encryption of the more widely used mode of CABAC-its regular mode. This allows encryption of a major codeword for video reconstruction, the prediction modes for intra blocks/units. Disturbing their statistics may cause bitrate overhead, which is the tradeoff for improving the content security level of the SE approach. A comprehensive study of this compromise between the improvement in the scrambling efficiency and the undesirable aftereffects is presented in this paper, and a specific security analysis of the proposed CABAC regular mode encryption is conducted.

Super Resolution (SR) addresses the problem of image and video upscaling. Most of the best performing SR methods do not take into account any compression prior into the degradation model. Consequently, compression artifacts can be undesirably amplified during SR. In the present work, we propose a novel HEVC-dedicated approach for embedding SR results into a domain that closely fits the compressed observation. Our main contribution is the inclusion of HEVC syntax (block size, quantization parameters etc.) into the degradation model. A recent convex optimization approach is used to solve the associated minimization problem. Over a wide range of resolutions and bitrates, we show that our method improves the results obtained with state of the art SR.

Low-bitrate video compression is a challenging task, particularly with the increasing complexity of video sequences. Re-shaping video data before its compression with modern hybrid encoders has provided interesting results in the low and ultra-low bit rate domains. In this work, we propose a novel saliency guided preprocessing approach, which combines adaptive re-sampling and background texture removal, to achieve efficient ROI-oriented compression. Evaluated with HEVC, we show that our solution improves the ROI encoding over a wide range of resolutions and bit rates whilst maintaining a high background intelligibility level.

Selective encryption designates a technique that aims at scrambling a message content while preserving its syntax. Such an approach allows encryption to be transparent towards middle-box and/or end user devices, and to easily fit within existing pipelines. In this paper, we propose to apply this property to a real-time diffusion scenario - or broadcast - over a RTP session. The main challenge of such problematic is the preservation of the synchronization between encryption and decryption. Our solution is based on the Advanced Encryption Standard in counter mode which has been modified to fit our auto-synchronization requirement. Setting up the proposed synchronization scheme does not induce any latency, and requires no additional bandwidth in the RTP session (no additional information is sent). Moreover, its parallel structure allows to start decryption on any given frame of the video while leaving a lot of room for further optimization purposes.

This paper presents a novel approach for real-time encryption of both H.264 and HEVC encoded streams. Our method relies on structure-preserving Selective Encryption (SE) managed by a symmetric ciphering/deciphering transcoder. Developped as an autonomous tool, it can be implemented within any existing software and hardware architecture and requires very low computational cost. The Advanced Encryption Standard (AES) manages the encryption step to guarantee the protection of encrypted streams. Our method preserves source format and overall bitrate, which ensures undetectable ciphering and suitability for streaming over heterogeneous networks. Experimental evaluation of our proposed transcoder is provided in this paper and a demonstrator of an implementation on a mobile device will support these theoretical results.

This paper proposes a global approach of JPWL (ISO/IEC 15444-11) image transmission over a realistic wireless channel able to ensure the best Quality of Service (QoS). In order to exploit the channel diversity, we consider a Closed-Loop MIMO-OFDM scheme with different precoder designs. In particular, the high flexibility of QoS precoder allows taking into account the scalability of JPWL jointly with the instantaneous MIMO channel status. This increases the visual quality of received images. The monitoring of the quality is made by a reduced-reference metric (QIP) based on object's saliency and interest point, both linked to human perception. It is performed in association with a robust JPWL decoder to determine the optimal decoding configuration in terms of PSNR. The proposed scheme provides very good results and its performance is shown through a realistic wireless channel.

In this paper, packet-level coding is considered in the framework of H.264/AVC video transmission. Two distinct solutions are proposed and compared in different realistic communication scenarios. The first is based on classical Reed-Solomon (RS) codes applied at the RTP layer, while the second on modern LDPC codes implemented at the UDP-Lite layer. An end-to-end Quality of Experience (QoE) evaluation is presented, in terms of achieved peak signal-to-noise power ratio (PSNR). Our numerical results show that, in low-latency video applications across communication channels introducing errors and erasures, the adoption of a packet-level coding scheme becomes essential to guarantee a satisfactory quality. The solution based on LDPC codes exhibits better performances in presence of severe packet loss rates.

In this paper, we propose an extrinsic distortion-based source-channel allocation for JPWL transcoding systems. The distortion based approach is possible thanks to the extrinsic distortion estimation using information contained in the compressed bitstream. The proposed estimation method gives a coarse grain estimator of the true distortion, but keeping the same relative order of magnitude for distortion. Although coarse, this estimation can be used efficiently in a distortion based source-channel allocation strategy. Simulation results are provided in the context of JPEG2000 bitstream wireless transmissions using JPWL tools.

This paper presents an original solution to efficiently transmit video bitstreams over an IP networked wireless channel via an unequal rate allocation protection scheme. The originality of this scheme is that it proposes a sensitivity estimation not only for the video stream itself as clasically done, but also for the network headers used over the IP wirless network, here considered in their compressed version. Based on this sensitivity measure, the protection allocation algorithm is able to propose an efficient unequal rate allocation scheme using rate compatible punctured codes. Numerical results obtained in the case of H.263+ bitstreams transmitted over an error prone wireless compressed RTP/UDP/IP network show that taking into account both video and headers sensitivity allows this Unequal Error Protection (UEP) scheme to provide PSNR improvements of about 5 dB when compared to Equal Error Protection (EEP) scheme with a low additional complexity.

A simple method is proposed to optimise the protection levels on the different parts of an H.264/AVC bitstream for transmission over an error-prone channel. This method relies on a semi-analytical model of the video stream sensitivity, that allows to predict the resulting distortion depending on the channel errors viewed by the video decoder. Valid for a frame, a partition or a group of pictures (GOP) by taking into account the dependencies existing between partitions and frames, the model allows to set the adapted protection for each partition or frame to minimise the overall sequence distortion for a given erroneous context by joint source channel optimisation of the compression and protection mechanisms. The method is then applied to determine the best trade-off of channel and source coding rates for a given operating point or protection rate, with equal or unequal error protection

The paper presents a solution of temporal scalability for video encoded H.264/MPEG-4 AVC bitstreams. Achieved through the concept of adaptive M-band hierarchical filterbanks, the temporal scalability is performed thanks to the application of a frame shuffling operation which allows backward compatibility with the standard to be kept. Simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality.

This paper presents a novel selective encryption scheme that allows for secure transmission of video streams such as H.264/AVC ones, while keeping complete backward compatibility with the corresponding video standard. This compatibility allows consequently any standard compliant decoder to decode the ciphered stream without specific provision in terms of resynchronization procedure, albeit incorrectly from the visual point of view. The bits to be encrypted are chosen with respect to the video standard, the full compatibility being achieved by encrypting bits for which the impact of each of the encrypted configurations gives a non-desynchronized and fully standard compliant bitstream. Numerical results obtained with this partial ciphering algorithm in the context of H.264/AVC show that PSNR degradations of about 25 to 30 dB are obtained when the ciphering key is unknown

This paper presents the application to H.264 standard of a soft-input VLC decoding algorithm based on MAP sequence estimation techniques and using residual source redundancy information to provide channel error protection and correction. This algorithm relies on the presence of soft values and of contextual information available at the input of the source decoder, and is fully compatible with the existing H.264 standard. Numerical results obtained with this considered soft-input decoding algorithm to the decoding of a H.264 encoded video sequence under the assumption of an unequal error protection scheme are presented. Performance obtained for the 'Foreman' ITU reference sequence show that the proposed algorithm provides gains up to 12 to 15 dB in terms of PSNR when compared to classical hard input decoding methods.