Transcoding Method Research Articles

An Effective DNA-Based File Storage System for Practical Archiving and Retrieval of Medical MRI Data.

DNA-based data storage is a new technology in computational and synthetic biology, that offers a solution for long-term, high-density data archiving. Given the critical importance of medical data in advancing human health, there is a growing interest in developing an effective medical data storage system based on DNA. Data integrity, accuracy, reliability, and efficient retrieval are all significant concerns. Therefore, this study proposes an Effective DNA Storage (EDS) approach for archiving medical MRI data. The EDS approach incorporates three key components (i) a novel fraction strategy to address the critical issue of rotating encoding, which often leads to data loss due to single base error propagation; (ii) a novel rule-based quaternary transcoding method that satisfies bio-constraints and ensure reliable mapping; and (iii) an indexing technique designed to simplify random search and access. The effectiveness of this approach is validated through computer simulations and biological experiments, confirming its practicality. The EDS approach outperforms existing methods, providing superior control over bio-constraints and reducing computational time. The results and code provided in this study open new avenues for practical DNA storage of medical MRI data, offering promising prospects for the future of medical data archiving and retrieval.

Memetic Algorithm with Isomorphic Transcoding for UAV Deployment Optimization in Energy-Efficient AIoT Data Collection

Unmanned aerial vehicles (UAVs) are one of the devices used to collect big data as part of the artificial intelligence of things (AIoT). To reduce total energy consumption, most researchers focus on optimizing the number and the location of UAVs, but ignore the distribution of UAVs in relation to the AIoT devices. Therefore, this paper proposes a memetic algorithm based on isomorphic transcoding space (MA-IT) to optimize the deployment of UAVs, solving, in particular, the distribution of UAVs in energy-efficient AIoT data collection. First, a simplified encoding method is designed to reduce the search space. This method only uses the distribution to represent a solution, and the number and the location of UAVs can be greedily deduced through the distribution. Afterwards, a pseudo-random initialization is proposed to initialize a population randomly and greedily. Then, an isomorphic transcoding (isoTcode) method is proposed to identify solutions with the isomorphic relations and to represent these solutions in a practical way in the UAV deployment problem. Finally, a crossover and a local search based on the isoTcode method are proposed to increase the solution diversity and improve the solution quality. Comparative experiments are conducted in the randomly generated instances with three problem scales. The results show that MA-IT performs better than other algorithms for solving the deployment optimization of UAVs.

An efficient video transcoding algorithm from h.264 to hevc

Video transcoding method usually reduces coding complexity with the cost of reducing coding efficiency. It is necessary to design a video transcoder can achieve a better trade-off between coding efficiency and complexity. This paper proposes an efficient video transcoder based on improved rate distortion optimization and improved motion vector (MV) reuse. First, we use an improved temporal dependent rate distortion optimization method to implement rate-distortion optimization (RDO) at the level of Coding Tree Units (CTUs). Second, we use improved motion vector reuse (IMVR) to reduce the complexity of encoding. Experimental results have shown that the proposed method can achieve an average reduction of 38.4% in the transcoding time with the cost of 0.6% BDBR increase compared with HEVC Test Model (HM) 16.9 encoder. It verifies that the proposed method can achieve a better trade-off between coding efficiency and complexity compared with existing transcoding methods.

Fast H.264 to HEVC Transcoding: A Deep Learning Method

With the development of video coding technology, high-efficiency video coding (HEVC) has become a promising alternative, compared with the previous coding standards, for example, H.264. In general, H.264 to HEVC transcoding can be accomplished by fully H.264 decoding and fully HEVC encoding, which suffers from considerable time consumption on the brute-force search of the HEVC coding tree unit (CTU) partition for rate-distortion optimization (RDO). In this paper, we propose a deep learning method to predict the HEVC CTU partition, instead of the brute-force RDO search, for H.264 to HEVC transcoding. First, we build a large-scale H.264 to HEVC transcoding database. Second, we investigate the correlation between the HEVC CTU partition and H.264 features, and analyze both temporal and spatial-temporal similarities of the CTU partition across video frames. Third, we propose a deep learning architecture of a hierarchical long short-term memory (H-LSTM) network to predict the CTU partition of HEVC. Then, the brute-force RDO search of the CTU partition is replaced by the H-LSTM prediction such that the computational time can be significantly reduced for fast H.264 to HEVC transcoding. Finally, the experimental results verify that the proposed H-LSTM method can achieve a better tradeoff between coding efficiency and complexity, compared to the state-of-the-art H.264 to HEVC transcoding methods.

Exploiting Pseudo-Quadtree Structure for Accelerating HEVC Spatial Resolution Downscaling Transcoder

In this paper, a novel method to accelerate the spatial resolution downscaling transcoding operation for high efficiency video coding (HEVC) is proposed. The proposed transcoder first extracts the information about the coding unit (CU) structure during the decoding process and analyzes it to construct a pseudo-quadtree of the target resolution. By utilizing the constructed pseudo-quadtree, the encoder process is accelerated by searching only the optimal depth in the quadtree structure. To evaluate the performance of the proposed transcoding method, its transcoding time and bitrate loss are measured and compared with those of the HEVC reference encoder and decoder. Also, a comparison with state-of-the-art fast CU size decision methods and spatial resolution downscaling transcoding methods for HEVC is presented. The proposed method achieves an average speedup of 1.65 with an average bitrate loss of 2.06%.

An efficient scheduling multimedia transcoding method for DASH streaming in cloud environment

As a result of technological evolution, streaming service providers have been dealing with the problem of delivery multimedia content to the diversity of devices with different resolutions. This issue can be solved by using dynamic adaptive streaming over hypertext (DASH) transfer protocol. However, a transcoding job in DASH requires a lot of computation resource which could lead to delaying the starting of multimedia streaming. Recently, new studies have addressed novel scheduling methods on video transcoding, but those research did not solve the problem entirely, such as the solution did not concern server performance or speed connection between a server and its requested users. Moreover, the load and speed connection status of the data servers is often unstable, leading to increasing the starting delay. So in this article, we solve such problem by modeling transcoding jobs in the form of an optimization problem and propose an algorithm to find an optimal schedule to transcode video source files. In which, we use moving average method to find average points for a short period to deal with server state changes. In the experiment, we implement our proposed method with DASH to demonstrate the effectiveness of the optimization scheduling method. In the system, we create several servers running on the Docker platform to simulate a cloud environment. Experimental results show that our methodology reduces the time of the transcoding process up to 30% compared to existing research.

Motion-Homogeneous-Based Fast Transcoding Method From H.264/AVC to HEVC

With the popularity of high-efficiency video coding (HEVC) standard, a video server usually transcodes a video stream to HEVC for its higher compression ratio. In this paper, a fast H.264/advanced video coding (AVC) to HEVC transcoding method is proposed. In the HEVC encoding procedure, a coding unit (CU), which is a motion-homogeneous block, is first checked based on the analysis of the decoded information from H.264/AVC bit stream. Then, for motion-homogeneous blocks, CU depth and the corresponding prediction unit (PU) mode's early termination strategies are proposed based on the CU size and corresponding prior statistical knowledge. For non-motion-homogeneous blocks, a corresponding PU mode's early termination strategy is also proposed. Experimental results demonstrate the effectiveness of the proposed method.

Transcoding method from H.264/AVC to high efficiency video coding based on similarity of intraprediction, interprediction, and motion vector

Currently, most video resources on line are encoded in the H.264/AVC format. More fluent video transmission can be obtained if these resources are encoded in the newest international video coding standard: high efficiency video coding (HEVC). In order to improve the video transmission and storage on line, a transcoding method from H.264/AVC to HEVC is proposed. In this transcoding algorithm, the coding information of intraprediction, interprediction, and motion vector (MV) in H.264/AVC video stream are used to accelerate the coding in HEVC. It is found through experiments that the region of interprediction in HEVC overlaps that in H.264/AVC. Therefore, the intraprediction for the region in HEVC, which is interpredicted in H.264/AVC, can be skipped to reduce coding complexity. Several macroblocks in H.264/AVC are combined into one PU in HEVC when the MV difference between two of the macroblocks in H.264/AVC is lower than a threshold. This method selects only one coding unit depth and one prediction unit (PU) mode to reduce the coding complexity. An MV interpolation method of combined PU in HEVC is proposed according to the areas and distances between the center of one macroblock in H.264/AVC and that of the PU in HEVC. The predicted MV accelerates the motion estimation for HEVC coding. The simulation results show that our proposed algorithm achieves significant coding time reduction with a little loss in bitrates distortion rate, compared to the existing transcoding algorithms and normal HEVC coding.

Machine learning based fast H.264/AVC to HEVC transcoding exploiting block partition similarity

Video transcoding is to convert one compressed video stream to another. In this paper, a fast H.264/AVC to High Efficiency Video Coding (HEVC) transcoding method based on machine learning is proposed by considering the similarity between compressed streams, especially the block partition correlations, to reduce the computational complexity. This becomes possible by constructing three-level binary classifiers to predict quad-tree Coding Unit (CU) partition in HEVC. Then, we propose a feature selection algorithm to get representative features to improve predication accuracy of the classification. In addition, we propose an adaptive probability threshold determination scheme to achieve a good trade-off between low coding complexity and high compression efficiency during the CU depth prediction in HEVC. Extensive experimental results demonstrate the proposed transcoder achieves complexity reduction of 50.2% and 49.2% on average under lowdelay P main and random access configurations while the rate-distortion degradation is negligible. The proposed scheme is proved more effective as comparing with the state-of-the-art benchmarks.

Big data-based multimedia transcoding method and its application in multimedia data mining-based smart transportation and telemedicine

The method and system proposed in this paper obtain different data and same data between current multimedia data and pre-stored data by comparing current multimedia data and pre-stored data and encode the attribute information of same data from encoding big data. It is not necessary to encode all multimedia data, but to encode different data and attribute information only. Different data account for a small proportion of the entire multimedia data, while same data represent most of the entire multimedia data. Besides, the encoding of same data is concerned with the attribute information of same data, so the quantity of encoding data is very small and hence the compression ratio is very higher.

Overlapping boundary based multimedia slice transcoding method and its system for medical video and traffic video

This paper is concerned about the field of multimedia transcoding technology. This paper provides a method for multimedia slice transcoding. This method is detailed as follows: the multimedia is segmented according to the preset unit to obtain large numbers of slices; the length of the slices' fuzzy area is acquired; both ends of each slice is made redundant for fuzzy area length; the slices after redundancy are transcoded; the redundant fuzzy area length at both ends of transcoded slice is cut; the slices of cut fuzzy area length are spliced. The method for multimedia slice transcoding stated in this paper can remove the boundary fuzzy area when the transcoded slices are spliced in order to obtain more satisfactory multimedia effects.

Method of Video Transcoding from MPEG-2 to HEVC with Picture Structure Information

Method of Video Transcoding from MPEG-2 to HEVC with Picture Structure Information

Parallel video transcoding using Hadoop MapReduce

Video transcoding has become a key technology for video content distribution network service. In this paper, we propose a novel MapReduce-based parallel video transcoding method. In our method, video files are stored on a shared file system to reduce the overhead of disks I/O and networks in the Hadoop MapReduce. FFmpeg is used to compute the splitting point of the video and the actual video transcoding. Experimental results show that our method can significantly reduce the time of transcoding.

Mobile Video-to-Audio Transducer and Motion Detection for Sensory Substitution

Visuo-auditory sensory substitution systems are augmented reality devices that translate a video stream into an audio stream in order to help the blind in daily tasks requiring visuo-spatial information. In this work, we present both a new mobile device and a transcoding method specifically designed to sonify moving objects. Frame differencing is used to extract spatial features from the video stream and two-dimensional spatial information is converted into audio cues using pitch, interaural time difference and interaural level difference. Using numerical methods, we attempt to reconstruct visuo-spatial information based on audio signals generated from various video stimuli. We show that despite a contrasted visual background and a highly lossy encoding method, the information in the audio signal is sufficient to allow object localization, object trajectory evaluation, object approach detection, and spatial separation of multiple objects. We also show that this type of audio signal can be interpreted by human users by asking ten subjects to discriminate trajectories based on generated audio signals.

Use of NTRIP for optimizing the decoding algorithm for real-time data streams.

As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (CORS), Wide Area Augmentation System (WAAS) and Satellite Based Augmentation Systems (SBAS). With the deployment of BeiDou Navigation Satellite system (BDS) to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG) NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX) format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.

Fast and Efficient Transcoding Based on Low-Complexity Background Modeling and Adaptive Block Classification

It is in urgent need to develop fast and efficient transcoding methods so as to remarkably save the storage of surveillance videos and synchronously transmit conference videos over different bandwidths. Towards this end, the special characteristics of these videos, e.g., the relatively static background, should be utilized for transcoding. Therefore, we propose a fast and efficient transcoding method (FET) based on background modeling and block classification in this paper. To improve the transcoding efficiency, FET adds the background picture, which is modeled from the originally decoded frames in low complexity, into stream in the form of an intra-coded G-picture. And then, FET utilizes the reconstructed G-picture as the long-term reference frame to transcode the following frames. This is mainly because our theoretical analyses show that G-picture can significantly improve the transcoding performance. To reduce the complexity, FET utilizes an adaptive threshold updating model for block classification and then adopts different transcoding strategies for different categories. This is due to the following statistics: after dividing blocks into categories of foreground, background and hybrid ones, different block categories have different distributions of prediction modes, motion vectors and reference frames. Extensive experiments on transcoding high-bit-rate H.264/AVC streams to low-bit-rate ones are carried out to evaluate our FET. Over the traditional full-decoding-and-full-encoding methods, FET can save more than 35% of the transcoding bit-rate with a speed-up ratio of larger than 10 on the surveillance videos. On the conference videos which should be transcoded more timely, FET achieves more than 20 times speed-up ratio with 0.2 dB gain.

보조정보의 움직임 벡터를 이용한 분산 비디오 코딩에서 H.264/AVC로의 트랜스코딩

In this paper, a transcoding method with low computational complexity and high coding efficiency is proposed to transcode distributed video coding (DVC) bitstreams to H.264/AVC ones. For the proposed high-performance transcoding with low complexity, not only Wyner-Ziv frames but also key frames can be transcoded with motion vectors estimated in generation of side information. As a motion vector is estimated from a key frame to a prior key frame for side information generation, the motion vector can be used to encode the intra key frame as a predicted frame. Motion estimation is performed with two predicted motion vectors. One is the motion vector from side information generation and the other is median of motion vectors of neighboring blocks. The proposed method selects the best motion vector between two motion vectors based on rate-distortion optimization. Coding efficiency can be improved with a small size of search range, because a motion vector estimated in side information generation is used as an initial motion vector for transcoding. In the experimental results, complexity of transcoder is reduced about 12% and bitrate performance increases about 28.7%.

An efficient transcoding algorithm between AMR-NB and G.729ab

In this paper, an efficient transcoding algorithm between AMR-NB and G.729ab is proposed. The proposed algorithm further elaborates on solutions when a DTX function is adopted between the source and destination coding systems. When neither, either or both of the source and destination coding systems adopt the DTX function, the proposed algorithm can carry out the transcoding operation between the two coding systems efficiently. When neither of the two coding systems adopts the DTX function, transcoding methods in different domains are proposed. A scalable distortion measure method based on parameter domain, specifically related to codebook gain conversion, is proposed to keep the amplitude of synthesized speech. The effect on subjective speech quality due to the amplitude of synthesized speech is cancelled out by using the proposed method and the computational complexity is reduced as well. When either or both of the two coding systems adopt the DTX function, depending on the type of the destination frame, transcoding methods between speech frames and non-speech frames are proposed. When the frame is declared as an erased frame, a linear prediction-based pitch recovery and transcoding method is used in this paper. By employing the proposed algorithm in transcoders, complexity is reduced by about 26–82% and quality is also improved compared to the conventional DTE method.

MPEG-2 Transcoding Method for Reducing Re-quantization Noise Based on a Two-tiered Quantizer Matrix

We developed an MPEG-2 transcoding method on the basis of a two-tiered quantizer matrix that reduces re-quantization noise. The proposed method changes the quantization matrix to decrease the re-quantization noise, instead of changing the value of the quantization parameters as conventional methods do. Using this two-tiered matrix makes it possible to reduce re-quantization noise in the high-frequency domain. The main feature of the proposed method is that it does not cause any differences in image quality between adjacent macroblocks, which the conventional method does. Experimental results show that our proposed method produces transcoding scores of structural similarity (SSIM) and video quality model (VQM) that are 0.044 and 0.0938, respectively, better than those of the best conventional method. The proposed method always produced superior SSIM and VQM scores when the bit reduction ratio was smaller than 0.1015 for all the tested sequences.

MPEG-2 Transcoding Method for Reducing Re-quantization Noise Based on a Two-tiered Quantizer Matrix

We developed an MPEG-2 transcoding method on the basis of a two-tiered quantizer matrix that reduces re-quantization noise. The proposed method changes the quantization matrix to decrease the re-quantization noise, instead of changing the value of the quantization parameters as conventional methods do. Using this two-tiered matrix makes it possible to reduce re-quantization noise in the high-frequency domain. The main feature of the proposed method is that it does not cause any differences in image quality between adjacent macroblocks, which the conventional method does. Experimental results show that our proposed method produces transcoding scores of structural similarity (SSIM) and video quality model (VQM) that are 0.044 and 0.0938, respectively, better than those of the best conventional method. The proposed method always produced superior SSIM and VQM scores when the bit reduction ratio was smaller than 0.1015 for all the tested sequences.