To achieve low-power video communication in Internet of Things, this study presents a new deep learning-based fast transcoding algorithm from distributed video coding (DVC) to high efficiency video coding (HEVC). The ...
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To achieve low-power video communication in Internet of Things, this study presents a new deep learning-based fast transcoding algorithm from distributed video coding (DVC) to high efficiency video coding (HEVC). The proposed method accelerates transcoding by minimizing HEVC encoding complexity. Specifically, it models the selections of coding unit (CU) partitions and prediction unit (PU) partition modes as classification tasks. To address these tasks, a novel lightweight deep learning network has been developed acting as the classifier in a top-down transcoding strategy for improved efficiency. The proposed transcoding algorithm operates efficiently at both CU and PU levels. At the CU level, it reduces HEVC encoding complexity by accurately predicting CU partitions. At the PU level, predicting PU partition modes for non-split CUs further streamlines the encoding process. Experimental results demonstrate that the proposed CU-level transcoding reduces complexity overhead by 45.69%, with a 1.33% average Bj & oslash;ntegaard delta bit-rate (BD-BR) increase. At the PU level, the transcoding achieves an even greater complexity reduction, averaging 60.97%, with a 2.16% average BD-BR increase. These results highlight the algorithm's efficiency in balancing computational cost and compression performance. The proposed method provides a promising low-power video coding scheme for resource-constrained terminals in both upstream and downstream video communication scenarios.
Inthis article, we considered dynamic video transcoding, leveraging Azure Functions’ serverless technology. In the theoretical and analytical part of the article, we explained concepts such as adaptive video transcod...
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ISBN:
(数字)9798331541811
ISBN:
(纸本)9798331541828
Inthis article, we considered dynamic video transcoding, leveraging Azure Functions’ serverless technology. In the theoretical and analytical part of the article, we explained concepts such as adaptive video transcoding, serverless architecture, and serverless functions. We analyzed the products of serverless service providers as well as their solutions to the video transcoding problem. We searched for and analyzed existing or similar solutions. Based on the results of the analytical part, in the second part of the article, we proposed our own solution to this problem. In the practical part of our work, we described the implementation of our proposed solution and discussed its testing and evaluation. We evaluated this solution both technically and economically by comparing it with competing video transcoding solutions. We presented our solution in the form of a web application that dynamically adjusted video parameters based on various cues.
Video transcoding is essential for multimedia processing as it enhances transmission efficiency, supports a variety of devices, and improves the user's experience. However, the output from the initial encoder is o...
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ISBN:
(数字)9798331534714
ISBN:
(纸本)9798331534721
Video transcoding is essential for multimedia processing as it enhances transmission efficiency, supports a variety of devices, and improves the user's experience. However, the output from the initial encoder is often unfriendly to subsequent transcoding. Existing transcoding optimization methods focus either concentrate on the initial encoding or the subsequent transcoding, neglecting the interplay between the two, even though both encoders significantly impact the overall transcoding process. In this work, we propose a processing network that bridges the initial encoding and subsequent transcoding, enabling a joint optimization of the transcoding process. For the initial encoder, considering the areas with lower residuals typically have smaller quantization losses, whereas areas with higher residuals do not, we employ residuals to guide the network in restoring compression distortion. In parallel, for the joint optimization of the subsequent encoder and the processing network, considering areas with large quantization losses typically indicate that the original region's distribution is either unsuitable for encoding or has complex textures, we have developed a corresponding mask in the DCT domain, and employ the quantified loss distribution from the subsequent encoder to fine-tune the loss training of the processing network. See Figure 1 for more details. Experiments show substantial enhancements in transcoding performance when transitioning from H.264 to H.265.
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 effici...
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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. (C) 2016 SPIE and IS&T
Forthcoming interactive video services such as video on demand will use pre-encoded bit streams for transmission. A great lack of flexibility arises when heterogeneous networks are used or when the user is allowed to ...
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Forthcoming interactive video services such as video on demand will use pre-encoded bit streams for transmission. A great lack of flexibility arises when heterogeneous networks are used or when the user is allowed to use a bandwidth of his/her own choice. In the paper, a mechanism capable of decoupling video encoders from transmission-network constraints and user demands is proposed. The authors devise a low-cost, low-delay video transcoder capable of providing transmission flexibility to pre-encoded bit streams, by reducing their bit rates according to either channel capacity or user demand. Simple techniques such as open-loop coarse requantisation or drop of high-frequency transform coefficients are shown to be inefficient, because of the drift introduced in the transcoded pictures. It is shown that transcoded pictures are drift-free and their quality, on average, is only about 1 dB worse than those directly encoded at the same bit rate. The proposed transcoder is far less complex than a cascade of decoder-encoder, while the picture quality is shown to be better for almost all frames.
We investigate transcoding of GIF images to JPEG-LS, the new lossless image compression standard. A straight forward conversion can lead to file sizes that are significantly larger than-the size of the corresponding G...
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We investigate transcoding of GIF images to JPEG-LS, the new lossless image compression standard. A straight forward conversion can lead to file sizes that are significantly larger than-the size of the corresponding GIF file. In this paper we show that suitable reordering of the color table leads to file sizes significantly smaller than those required by the GIF format.
Scalable video coding (SVC) enables low complexity adaptation of compressed video, providing an efficient solution for content delivery through heterogeneous networks and to diverse displays. However, legacy video and...
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Scalable video coding (SVC) enables low complexity adaptation of compressed video, providing an efficient solution for content delivery through heterogeneous networks and to diverse displays. However, legacy video and most commercially available content capturing devices use conventional nonscalable coding, e.g., H.264/AVC. This paper proposes an efficient transcoder from H.264/AVC to a wavelet-based SVC. It aims at exploiting the advantages offered by fine granularity SVC technology when dealing with conventional coders and legacy video. The proposed transcoder was developed to cope with important functionalities of H.264/AVC, such as flexible reference frame (RF) selection. It is able to work with different coding configurations of H.264/AVC, including IPP or IBBP with multiple RFs. Moreover, many of the techniques presented in this paper are generic in the sense that they can be used for transcoding with many popular wavelet-based and hybrid-based video coding architectures. To reduce the transcoder's complexity, motion information and residual data extracted from a compressed H.264/AVC stream are exploited. Experimental results show a very good performance of the proposed transcoder in terms of decoded video quality and system complexity.
This paper discusses the problem of transcoding as it may occur in, for instance, the following situation. Suppose a satellite transmits an MPEG-compressed video signal at say 9 Mbit/s. This signal must be relayed at ...
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This paper discusses the problem of transcoding as it may occur in, for instance, the following situation. Suppose a satellite transmits an MPEG-compressed video signal at say 9 Mbit/s. This signal must be relayed at a cable head end. However, since the cable capacity is only limited, the cable head end will want to relay this incoming signal at a lower bit-rate of, say, 5 Mbit/s. The problem is how to convert a compressed video signal of a given bit-rate into a compressed video signal of a lower bit-rate. The specific transcoding problem discussed in this paper is referred to as bit-rate conversion. Basically, a transcoder used for such a purpose will consist of a cascaded decoder and encoder. It is shown in the paper that the complexity of this combination can be significantly reduced. The paper also investigates the loss of picture quality that may be expected when a transcoder is in the transmission chain. The loss of quality as compared to that resulting in the case of transmission without a transcoder is studied by means of computations using simplified models of the transmission chains and by means of using computer simulations of the complete transmission chain. It will be shown that the presence of two quantizers, i.e. cascaded quantization, in the transmission chain is the main cause of extra losses, and it will be shown that the losses in terms of SNR will be some 0.5-1.0 dB greater than in the case of a transmission chain without a transcoder.
Mobile devices and accessing the web have become essential in our daily lives. However, their limitations in terms of both hardware such as the battery, and software capabilities can affect the user experience such as...
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Mobile devices and accessing the web have become essential in our daily lives. However, their limitations in terms of both hardware such as the battery, and software capabilities can affect the user experience such as battery drain. There are some best practices for the web page design that are shown to affect the downloading time of web pages. In this study, we report our experience in applying these practices to see their effect on energy saving. We propose two techniques: (1) concatenating external script and stylesheet files and (2) minifying external script and stylesheets that can be used to transcode web pages to improve energy consumption on the client-side and therefore improve the battery life. We present our experimental architecture, implementation, and a systematic evaluation of these two techniques. The evaluation results show that the proposed techniques can achieve approximately 12% processor energy-saving and 4% power saving in two different client types, 13% improvement in a typical laptop battery life, and 4% improvement in a typical mobile phone battery life.
transcoding is the process of translating between spoken and written numbers, and it is correlated with other mathematical skills. In the present study, we investigated the link between French number writing of 49 stu...
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transcoding is the process of translating between spoken and written numbers, and it is correlated with other mathematical skills. In the present study, we investigated the link between French number writing of 49 students in the third grade (aged 7-9 years) and their language skills. transcoding in French is of particular interest because the spoken number language system does not completely correspond to that of the written digits (e.g., quatre-vingt-dix [four-twenty-ten] and 90). We hypothesised that the complex linguistic structure of spoken numbers in French would be challenging for students who are learning to transcode. First and second French-language learners' accuracy and errors were recorded during a writing task of 3- to 7-digit numbers. Children also completed linguistic tests (e.g., receptive vocabulary, receptive syntax). Results showed that first- and second-language learners did not differ in their transcoding accuracy. Number size, decade complexity of stimulus number words in French (i.e., numbers containing a complex decade, operationalized as a number between soixante-dix, 70, and quatre-vingt-dix-neuf, 99), and receptive vocabulary predicted children's French transcoding skills. Students were more likely to produce errors (e.g., 68 or 6018 for 78) when they transcoded complex decade numbers compared with simple decade numbers. When an error was made on the complex decade portion of a number, it was likely a lexical error. In conclusion, third graders, both first- and second-language learners, found complex decade numbers challenging and their performance was related to their general vocabulary skills.
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