Macroblock Research Articles

Real-time motion estimation based video steganography with preserved consistency and local optimality

AbstractThis paper introduces a novel steganographic technique for H.264 video that achieves an outstanding performance against state-of-the-art steganalysis techniques while maintaining real-time encoding performance constraints. The proposed technique embeds the secret message by altering the motion vectors (MVs) while preserving their local optimality and consistency feature to withstand the recently emerged steganalysis methods. Thanks to its macro-block (MB) basis architecture, the proposed technique satisfies the real-time constraints, eliminating the need to wait for the whole frame or group of pictures (GOP) and avoiding the need to perform any additional re-encoding step(s). Additionally, altering the MVs is performed in the motion estimation (ME) sub-pixel-refinement stage through a rule-based scheme that ensures each MB’s compatibility for embedding without detection by the aforementioned steganalysis methods. The proposed technique is integrated with the OpenH264 real-time video encoder and evaluated on widely used video sequences. The results prove that the proposed technique achieves a significant security performance against the steganalysis methods while maintaining an acceptable embedding rate, outperforming other state-of-the-art MV-based steganographic methods in real-time constrained environments. The proposed technique adds about $$1-2\%$$ 1 - 2 % overhead beyond the encoder running time. The source code is publicly available here: https://github.com/HassanMohamedGit/OpenH264-RealTime-steg.

Integrated Power Distribution Network Synthesis for Mixed Macro Blocks and Standard Cells

Power distribution network (PDN) requires more routing resources as wire resistance increases with technology scaling but IR drop constraint does not scale. We address post-placement PDN synthesis for mixed macro blocks and standard cells. Macro blocks already have partial PDN, while standard cells do not. So the design, which has been placed, is divided into a number of partitions: each macro block in its own partition, and standard cell area into a number of partitions. Multi-layer PDN synthesis is performed in each partition one by one; the goal of this problem is to insert minimum number of metal straps (in irregular pitches) while IR drop and electromigration (EM) constraints are respected. This is formulated as mixed integer quadratically constrained programming (MIQCP) and a heuristic algorithm is proposed for practical application. Experimental results with some test circuits indicate that the proposed approach achieves on average of 26% reduction in PDN straps, which helps reduce congestion overflow of signal routing by 15%, compared to popular approach in which PDN straps are located in regular pitch period.

Binocular Rivalry Impact on Macroblock-Loss Error Concealment for Stereoscopic 3D Video Transmission

Three-dimensional video services delivered through wireless communication channels have to deal with numerous challenges due to the limitations of both the transmission channel's bandwidth and receiving devices. Adverse channel conditions, delays, or jitters can result in bit errors and packet losses, which can alter the appearance of stereoscopic 3D (S3D) video. Due to the perception of dissimilar patterns by the two human eyes, they can not be fused into a stable composite pattern in the brain and hence try to dominate by suppressing each other. Thus, a psychovisual sensation that is called binocular rivalry occurs. As a result, undetectable changes causing irritating flickering effects are seen, leading to visual discomforts such as eye strain, headache, nausea, and weariness. This study addresses the observer's quality of experience (QoE) by analyzing the binocular rivalry impact on the macroblock (MB) losses in a frame and its error propagation due to predictive frame encoding in stereoscopic video transmission systems. To simulate the processing of experimental videos, the Joint Test Model (JM) reference software has been used as it is recommended by the International Telecommunication Union (ITU). Existing error concealing techniques were then applied to the contiguous lost MBs for a variety of transmission impairments. In order to validate the authenticity of the simulated packet loss environment, several objective evaluations were carried out. Standard numbers of subjects were then engaged in the subjective testing of common 3D video sequences. The results were then statistically examined using a standard Student's t-test, allowing the impact of binocular rivalry to be compared to that of a non-rivalry error condition. The major goal is to assure error-free video communication by minimizing the negative impacts of binocular rivalry and boosting the ability to efficiently integrate 3D video material to improve viewers' overall QoE.

Tasmanian Devil Sail Fish Optimization with Deep Learning Enabled Macro Block Selection for Video Steganography in Compressed Video Stream

Tasmanian Devil Sail Fish Optimization with Deep Learning Enabled Macro Block Selection for Video Steganography in Compressed Video Stream

A Comparison of MB-CBFM and Modified ASED Basis Function Method to Analyze Interconnected Finite Periodic Arrays

This letter compares the macro block-characteristic basis function method (MB-CBFM) with the modified accurate subentire-domain (ASED) basis function method to solve the interconnected finite periodic arrays. In the MB-CBFM, a compressed matrix equation whose size is less than that of the conventional CBFM can be obtained using the idea of macro blocks and the array theory. In the modified ASED method, a few sets of ASED bases on the cells are constructed by solving the subarray problem excited by the several plane waves. Afterwards, a reduced matrix equation will be obtained. The size of the matrix is greater than that in the MB-CBFM for the large-scale arrays. Numerical results obtained from the modified ASED basis function method are more accurate than those of the MB-CBFM.

A Novel Video Steganographic Scheme Incorporating the Consistency Degree of Motion Vectors

In this letter, a novel steganographic scheme in motion vector domain (MV) for H.264 video is presented, which can significantly improve the security performance against the newly emerged powerful multi-domain feature set MVC (motion vector consistency). By taking into account both the consistency degree of motion vectors for sub-blocks within a macroblock (MB) or sub-macroblock (sub-MB), and the MV statistics, the corresponding distortion function called dMVC is proposed. The proposed dMVC is also shown to be capable of integrating with existing methods to resist the joint steganalytic attacks of both MVC feature and local optimality features, e.g., NPELO, in the framework of minimal distortion embedding. Compared with other state-of-the-art MV-based steganographic schemes, experimental results on YUV sequences at various embedding rates and QPs show that the proposed method gains significant performance improvement while maintaining good coding efficiency.

Penerapan Metode Delta Modulation dalam Kompresi File Video Mp4

The development of digital technology shows very rapid progress. This development is also closely related to the availability of the storage media needed for data storage. This need is due to the fact that more and more data is stored, and the size of the data is large. Compression is a technique to reduce the amount of data size from the original data. The general principle used in the video compression process is to reduce duplication of data in the video so that the memory needed to represent the original video. Many of the videos that are produced contain duplicate data. In this study, the authors applied the Delta Modulation method to perform MP4 videos. This method will compress by grouping pixels into 8x8 macro blocks. And added with the quantity process to shrink the pixel value, so that the Delta Modulation process works better on compressed MP4 videos.

CAD synthesis tools for floating-gate SoC FPAAs

We present a tool framework to compile and program mixed-signal circuits and systems on Floating-Gate (FG) based mixed-signal System-on-Chips (SoC) consisting of a digital processor and Field Programmable Analog Array (FPAA) fabric. We have modified the configuration of Verilog-to-Routing (VTR) to cover analog circuits and developed a tool called vpr2swcs to create the list of FG switches, that is going from a high level block description of the system to the addresses and bias values on the SoC. This tool enables users to generate macro blocks and customize block location while designing mixed-signal systems on the FPAA and also enables using routing fabric, composed of FGs, for Vector Matrix Multiplication (VMM), a computing element for an analog neural network. The paper demonstrates system level examples using this tool flow, where the experimental results have been proved in other publications.

Improved Hybrid Block-Based Motion Estimation for Inter-frame Coding

Digital video technology has been increasingly needed in various fields, such as telecommunications, entertainment, medicine. Therefore, video compression is required. Motion estimation methods help in improving video compression efficiency by effectively removing the temporal redundancy between successive frames. Several block-based motion estimation (BME) algorithms are being suggested to reduce the coding process’s computational complexity. This paper proposes a new rapid hybrid (BME) algorithm established on the primary search point prediction and advance ending search point strategies. It combines rough adaptive search and effective local search. The coarse search introduces a new motion vector (MV) prediction technique that utilizes the macro-blocks (MBs) Spatio-temporal correlations to optimize the traditional adaptive-rood-pattern search algorithm (ARPS) and speeding up the whole process without affecting the accuracy. In the accurate local search, the cross-formed search pattern using a one-step search (OSS) block matching algorithm is employed, to estimate the actual (MV) with less computation time and further speed up the search efficiency. Exhaustive experiments are performed to demonstrate the present algorithm’s performance over the benchmark schemes concerning specific assessment criteria for results, including the peak signal-to-noise ratio (PSNR), computational complexity and computational gain. The results show that the proposed algorithm is efficient and reliable; it can always give better performance over diamond search (DS) and (ARPS). The conducted test shows an increased performance of search speed while preserving the visual quality of the motion-compensated images, and it achieves 59.76–88.03 speed improvement over (DS) and 20.98–72.06 over (ARPS) for different video sequences. Besides, the suggested method (ARP-OSS) provides the best result compared to (DS) and (ARPS) in terms of time complexity for analyzing all the video samples.

Content-based hybrid error concealment approach for packet video communication over the noisy channels

Video compression makes the encoded video stream more vulnerable to the channel errors so that, the quality of the received video is exposed to severe degradation when the compressed video is transmitted over the error-prone environments. Therefore, it is necessary to apply error concealment (EC) techniques in the decoder to improve the quality of the received video. In this regard, an Adaptive Content-based EC Approach (ACBECA) is proposed in this paper, which exploits both the spatial and temporal correlations within the video sequences for the EC purpose. The proposed approach adaptively utilizes two EC techniques, including new spatial-temporal error concealment (STEC) technique, and a temporal error concealment (TEC) technique, to recover the lost regions of the frame. The STEC technique proposed in this paper is established on the basis of non-Local Means concept and tries to recover each lost macroblock (MB) as the weighted average of the similar MBs in the reference frame, whereas the TEC technique recovers the motion vector of the lost MB adaptively by analyzing the behavior of the MB in the frame. The decision on temporally or spatially reconstructing the degraded frames is made dynamically according to the content of the degraded frame (i.e., structure or texture), type of the error and also block loss rate (BLR). Compared with the state-of-the-art EC techniques, the simulation results indicate the superiority of the ACBECA in terms of both the objective and subjective quality assessments.

Fast Wideband Monostatic Scattering Analysis Method Combining Macro-Block Characteristic Basis Function Method With Improved FIR for Freestanding Large-Scale Finite Periodic Arrays

An efficient numerical method for the wideband scattering analysis of the freestanding large-scale finite periodic array is presented using the macro block-characteristic basis function method (MB-CBFM) and the improved frequency-independent reaction (FIR). In the MB-CBFM, the blocks (unit cells) are divided into some types of macro blocks. By analyzing the subarray with the macro blocks, the CBFs for the macro blocks will be obtained. The blocks in the same macro block share the same CBFs. Substituting the CBFs into the moment matrix equation, a reduced matrix equation whose size does not depend on the number of the blocks can be obtained and handled utilizing direct methods. When the MB-CBFM is applied for wideband analysis, the matrix needs to be recomputed. The reduced matrix can be efficiently generated by using the improved FIR, in which the matrix elements are expressed as the product of the geometrical elements and the phase factor. The geometrical elements are computed one time and reused. Only the phase factor needs to be recomputed. Several numerical examples are carried out. Simulation results show that the results of the proposed algorithm agree well with those of other numerical methods. The total CPU time is significantly reduced.

An Effective Burst Access Scheme for Lossless Frame Buffer Compression on a Video Decoder

For decoding high-resolution image stored in external memory after lossless compression, it is inevitable necessary to allow variable-length data types and this may decreases the efficiency in real time read of arbitrary compressed macro block without burst-mode in memory. This paper proposes a cache architecture for a video decoder that has a burst mode capability for accessing lossless compressed frame data in the memory. In the proposed cache architecture, the write and read caches employ the concept of fixed-length burst groups, allowing efficient burst write and read operations. The experimental results show that the proposed cache architecture can decrease memory access times by an average of 70.92%

Motion estimation using variable size block matching with cross square search pattern

In recent decades, motion estimation is a major concern in video coding applications. Among all existing techniques, block matching is an emerging technique in motion estimation, because of its simplicity and effectiveness for both hardware and software implementations. In addition, the block matching technique helps in choosing the motion vectors for every macro block instead of utilizing a motion vector for every pixel. In this research article, Variable Size Block Matching (VSBM) with cross square search pattern is proposed for motion estimation in the videos. Compared to other block matching methods, the VSBM results in a low motion compensation error and also significantly speed up the motion estimation process. For reducing the illumination change effect in the video frame, cross square search pattern is developed that prevents macro blocks from over-splitting. In this work, the proposed algorithm performance is analysed by using some real time videos like container, Akiyo, Stefan, kristen-sara, foreman, Johnny, old-town-cross, Carphone, football and crowd-run. From the analysis, the proposed algorithm results in maximum of 14.9 dB improvement in peak signal to noise ratio value as compared to existing algorithms; dynamic pattern (square, diamond and hexagon) and harmony search with block matching.

A Low Complex Selective Block Correlation for Video Frame Interpolation

This paper presents a new frame interpolation technique based on correlation between non overlapping macro blocks. The proposed algorithm generates correlation values and identifies the median value as threshold amongst them. The blocks with correlation less than threshold are linearly interpolated. By linear interpolation between blocks reduces artifacts due to occlusions and holes caused by Motion Vector (MV) processing. Our algorithm decreases the computational complexity to minimum. Experimental results demonstrate that our proposed algorithm performs well in terms of SSIM and computational complexity compared to existing algorithms.

Motion vector based video steganography using homogeneous block selection

In recent steganographic literature, video steganography becomes popular due to its capability of accommodating higher payload. Since the video is transmitted mostly in a compressed format, compressed domain parameters are a natural choice for data embedding. In this paper, a motion vector based video steganographic method is proposed. For embedding the secret bit stream, the embedding motion vectors are selected for the homogeneous regions of the reference frame. Since homogeneous or smooth regions contain macro blocks with similar prediction error blocks, it helps to reduce the chance of detection by masking the embedding noise with similar prediction error among neighbouring macro blocks. The efficient search window and polar orientation based embedding technique are used to improve the imperceptibility against standard steganalysis schemes. A set of experiments is been carried out to justify the efficacy of the proposed scheme over the related existing steganographic methods.

Research on Video Encryption and Privacy Protection in Cloud Monitoring System Based on H.264

: Cloud monitoring technology is an important maintenance and management tool for cloud platforms.Cloud monitoring system is a kind of network monitoring service, monitoring technology and monitoring platform based on Internet. At present, the monitoring system is changed from the local monitoring to cloud monitoring, with the flexibility and convenience improved, but also exposed more security issues. Cloud video may be intercepted or changed in the transmission process. Most of the existing encryption algorithms have defects in real-time and security. Aiming at the current security problems of cloud video surveillance, this paper proposes a new video encryption algorithm based on H.264 standard. By using the advanced FMO mechanism, the related macro blocks can be driven into different Slice. The encryption algorithm proposed in this paper can encrypt the whole video content by encrypting the FMO sub images. The method has high real-time performance, and the encryption process can be executed in parallel with the coding process. The algorithm can also be combined with traditional scrambling algorithm, further improve the video encryption effect. The algorithm selects the encrypted part of the video data, which reducing the amount of data to be encrypted. Thus reducing the computational complexity of the encryption system, with faster encryption speed, improve real-time and security, suitable for transfer through mobile multimedia and wireless multimedia network.

Modified Boundary Matching algorithm for Error detection and Error Concealment for Video Communication

As the demand of video transmission over communication network has grown rapidly, the data compression and error correction in video processing have shown significant improvement day by day. When the error occurs in a single frame, the visual quality of the subsequent frames gets degraded due to error propagation. Thus, the error control techniques are required for the recovery. Concealment of error at the receiver (decoder) side feats the spatial and temporal characteristics of the frame. Without the requirement of the extra bandwidth and retransmission delay, it enhances the quality of the reconstructed video. However, the output of the error concealment may get affected if the error located before is misleading. Thus error detection also plays an important role while reconstructing the video. However, the output of the error concealment may get affected if the error located before is misleading. This paper proposes error detection and concealment approach for the recovery of lost Macro Block (MB) in video. The spatio-temporal techniques has been used for the error detection followed by the MB type decision applied for classifying the damaged macro block .For the concealment method a new method i.e. Modified Spatio-Temporal Boundary Matching Algorithm (MSTBMA) has been proposed. The proposed work is compared with various existing method for spatial and temporal error concealment. The comparison has been done for various types of error such as block error (single, multiple), burst error and random error generated by the software. Performance is improves in terms of PSNR and visual quality by considering the type of lost MB.

Improved Logarithmic Search for Efficient Video Compression

For efficient video compression, the BMAs should be designed and implemented in such a way that that the Motion Estimation takes very less time and will have lesser complexity. In this paper, two new algorithms namely Improved Logarithmic Search (ILS) and Zero motion predicted ILS (ZMILS) are proposed which are based on the basic idea of Three Steps Search (TSS) algorithm. In these BMA, the search pattern of proposed algorithms changes the efficiency both in terms of complications required for each macro block (MB) and quality of the compensated images. We improved the TSS and NTSS by changing the searching pattern of locations in reference frame and by adding no movement early prediction case with these algorithms we further reduced the computations. The computations required by the new developed algorithm are lesser per macro block and even 50% of few existing techniques while retaining the quality of the reconstructed image.

A robust blind watermarking framework based on Dn structure

In this paper, a new robust watermarking framework is designed using the discrete cosine transform (DCT), binary decimal sequence (d-sequence) and Dn-structure. The core idea is to generate a binary d-sequence based on random number generator (RNG) and some secret keys. This binary sequence is then utilized to generate reference sets based on Dn-structure. For embedding purpose, the host image is transformed using DCT and selected coefficients are employed to construct a macro block. Each binary watermark bit is securely embedded into macro block by utilizing the reference set. The reverse process is finally formulated to extract the watermark at the receiver end. The proposed technique is experimentally analyzed using various quality metrics and attacks. The comprehensive experimental results illustrate that the proposed watermarking scheme is robust to both geometric distortions (resizing, cropping, wrapping and random row deletion) and general signal processing attacks (various noise addition, blurring, high pass filtering, image sharpening, contrast adjustment, Histogram equalization and gamma correction and JPEG compression) and outperforms state-of-the-art watermarking methods.

Video Classification With CNNs: Using the Codec as a Spatio-Temporal Activity Sensor

We investigate video classification via a two-stream convolutional neural network (CNN) design that directly ingests information extracted from compressed video bitstreams. Our approach begins with the observation that all modern video codecs divide the input frames into macroblocks (MBs). We demonstrate that selective access to MB motion vector (MV) information within compressed video bitstreams can also provide for selective, motion-adaptive, MB pixel decoding (a.k.a., MB texture decoding). This in turn allows for the derivation of spatio-temporal video activity regions at extremely high speed in comparison to conventional full-frame decoding followed by optical flow estimation. In order to evaluate the accuracy of a video classification framework based on such activity data, we independently train two CNN architectures on MB texture and MV correspondences and then fuse their scores to derive the final classification of each test video. Evaluation on two standard data sets shows that the proposed approach is competitive with the best two-stream video classification approaches found in the literature. At the same time: 1) a CPU-based realization of our MV extraction is over 977 times faster than GPU-based optical flow methods; 2) selective decoding is up to 12 times faster than full-frame decoding; and 3) our proposed spatial and temporal CNNs perform inference at 5 to 49 times lower cloud computing cost than the fastest methods from the literature.