scholarly journals Analisis Perbandingan Teknik Video Codec H.264/AVC, H.265/HEVC, VP9 dan AV1

2021 ◽  
Vol 5 (2) ◽  
pp. 187-195
Author(s):  
Ayu Shafira Tubagus ◽  
◽  
Rizal Saepul Mahdi ◽  
Adhi Rizal ◽  
Aries Suharso ◽  
...  
Keyword(s):  
Video Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Video Codec ◽  
The Other ◽  
Compressed Video ◽  
File Size ◽  
Video Frames ◽  
Quality Video ◽  
Short Time

Video applications consume more energy on the Internet and can be accessed by electronic devices, due to an increase in the consumption of high-resolution and high-quality video content, presenting serious issues to delivery infrastructure that needs higher video compression technologies. The focus of this paper is to evaluate the quality of the most current codec, AV1, to its predecessor codec. The comparison was made experimentally at two video resolutions (1080p and 720p) by sampling video frames with various CRF/CQP values and testing several parameters analyses such as encoding duration, compression ratio, bit rate, Mean Square Error (MSE), and Peak Signal to Noise Ratio (PSNR). The AV1 codec is very great in terms of quality and file size, even though it is slower in terms of compression speed. The H.265/HEVC codec, on the other side, beats the other codec in terms of compression ratio. In conclusion, the H.265/HEVC codec is suggested as a material for obtaining a well compressed video with small file size and a short time.

scholarly journals Real-Time Layered Video Compression using SIMD Computation

1998 ◽  
Vol 5 (45) ◽  
Author(s):  
Morten Vadskær Jensen ◽  
Brian Nielsen
Keyword(s):  
Real Time ◽  
Video Compression ◽  
High Performance ◽  
Signal To Noise Ratio ◽  
Video Stream ◽  
Video Codec ◽  
Discrete Cosine Transforms ◽  
Wide Range ◽  
Layered Video ◽  
The Difference

We present the design and implementation of a high performance layered video codec, designed for deployment in bandwidth heterogeneous networks. The codec combines wavelet based subband decomposition and discrete cosine transforms to facilitate layered spatial and SNR (signal-to-noise ratio) coding for bit-rate adaptation to a wide range of receiver capabilities. We show how a test video stream can be partitioned into several distinct layers of increasing visual quality and bandwidth requirements, with the difference between highest and lowest requirement being 47 : 1. Through the use of the Visual Instruction Set on SUN's Ultra-SPARC platform we demonstrate how SIMD parallel image processing enables real-time layered encoding and decoding in software. Our 384 * 320 * 24-bit test video stream is partitioned into 21 layers at a speed of 39 frames per second and reconstructed at 28 frames per second. Our VIS accelerated encoder stages are about 3-4 times as fast as an optimized C version. We find that this speed-up is well worth the extra implementation effort.

New Approach of Encrypting Embedded Data in H.264 Compressed Video

2011 ◽  
Vol 230-232 ◽  
pp. 346-351
Author(s):  
Tarik Idbeaa ◽  
Kasmiran Jumari ◽  
Salina Abd. Samad ◽  
Ali Abdulgader ◽  
Nidal Eshah
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
Signal To Noise Ratio ◽  
Video Stream ◽  
Video Sequences ◽  
Compressed Video ◽  
Signal To Noise ◽  
New Approach ◽  
Video Steganography

Digital video steganography has attracted a great deal of research interest in the recent few years in applications. In this paper, we propose a method to embed and encrypt messages into video sequences by using steganography technique Based on the H.264 video coding standard. The system implemented in this work provides robust H.264 video compression constant, without significantly affecting the overall bit rate and quality of the video stream. The results indicate that the algorithm can be implemented steganography fast and efficiently and effect vision and peak signal to noise ratio (PSNR) of video sequences are almost unaffected after decoding.

scholarly journals Video Compression Based on FPGA Using SIMD Architecture

2021 ◽  
pp. 62-72
Keyword(s):  
Video Compression ◽  
Compression Ratio ◽  
Compressed Video ◽  
Video File ◽  
Large Size ◽  
Simd Architecture ◽  
Throughput Improvement ◽  
Real Value ◽  
Index Terms ◽  
Efficient Video

Recently, video files and images have became the dominant media material for transmitting or storing across different applications that are used by different people. So, there was a serious need to find more effective and efficient video compression techniques to reduce the large size of such multimedia files. This paper proposes SIMD based FPGA lossless JPEG video compression system with the facility of scalability. Generally, the proposed system consists of a software side and a hardware side. The digital video file is prepared to be processed by the hardware side frame by frame on the software side. The hardware side is proposed to consist of two main processing circuits, which are the prediction circuit for calculating the predicted value of each pixel in the certain frame and the encoding circuit that was represented by a modified RLE (Run-Length-Encoder) to encode the result obtained through subtracting the predicted value from the real value for each pixel to produce the final compressed video file. The compression ratio obtained for the proposed system is equal to 1.7493. The throughput improvement for the two and four processing units basing on SIMD architecture was 100 MP/s and 200 MP/s, respectively. The clock results showed that the number of clocks required had become 50% and 25% when using two processing units and four processing units, respectively, from the number of clocks using single processing units. Index Terms— Video Compression, Lossless JPEG, RLE, FPGA.

An Efficient Video Compression Technique Using Watershed Algorithm and JPEG-LS Encoding

2016 ◽  
Vol 13 (10) ◽  
pp. 6671-6679
Author(s):  
H Rajasekhar ◽  
B. Prabhakara Rao
Keyword(s):  
Motion Estimation ◽  
Video Compression ◽  
Compression Ratio ◽  
Estimation Algorithm ◽  
Huffman Coding ◽  
Compressed Video ◽  
Compression Method ◽  
Compression Process ◽  
Compression Technique ◽  
Motion Estimation Algorithm

In the previous video compression method, the videos were segmented by using the novel motion estimation algorithm with aid of watershed method. But, the compression ratio (CR) of compression with novel motion estimation algorithm was not giving an adequate result. Moreover this methods performance is needed to be improved in the encoding and decoding processes. Because most of the video compression methods have utilized encoding techniques like JPEG, Run Length, Huffman coding and LSK encoding. The improvement of the encoding techniques in the compression process will improve the compression result. Hence, to overcome these drawbacks, we intended to propose a new video compression method with renowned encoding technique. In this proposed video compression method, the input video frames motion vectors are estimated by applying watershed and ARS-ST (Adaptive Rood Search with Spatio-Temporal) algorithms. After that, the vector blocks which have high difference value are encoded by using the JPEG-LS encoder. JPEG-LS have excellent coding and computational efficiency, and it outperforms JPEG2000 and many other image compression methods. This algorithm is of relatively low complexity, low storage requirement and its compression capability is efficient enough. To get the compressed video, the encoded blocks are subsequently decoded by JPEG-LS. The implementation result shows the effectiveness of proposed method, in compressing more number of videos. The performance of our proposed video compression method is evaluated by comparing the result of proposed method with the existing video compression techniques. The comparison result shows that our proposed method acquires high-quality compression ratio and PSNR for the number of testing videos than the existing techniques.

scholarly journals Anisotropic Sophisticated Spatio-Temporal Contours Based Deep Neural Learned Moving Objects Detection in Video

2019 ◽  
Vol 8 (4) ◽  
pp. 7293-7300
Keyword(s):  
Object Detection ◽  
Video Compression ◽  
Moving Objects ◽  
Machine Learning Techniques ◽  
Compressed Video ◽  
Moving Objects Detection ◽  
Video Frames ◽  
Input Layer ◽  
Hidden Layer ◽  
Objects Detection

Object detection in the video sequence is a significant problem to be resolved in image processing because it used different applications in video compression, video surveillance, robot technology, etc. Few research works have been designed in conventional works to discover moving objects using various machine learning techniques. However, dynamic changing background, object size variations and degradation of video frames during the object detection process remained an open issue. In order to overcome such limitations, Anisotropic Sophisticated Spatiotemporal Contours based Deep Neural Network Learning (ASSC-DNNL) practice is projected. ASSC-DNL Technique initially obtains a number of video file as input at the input layer. After acquiring the video, input layer forward it to hidden layers. Subsequently, ASSC-DNL Technique accomplishes the encoding process in the first hidden layer using Anisotropic Stacked Autoencoder (ASA). During the encoding process, ASSC-DNL practice maps each video frames pixels in input video via code. This practice results in compressed video with enhanced quality. Afterward, ASSC-DNL practice transforms compressed video into a numeral of frames in the second concealed layer. Followed by, ASSC-DNL practice carried out Teknomo–Fernandez Spatiotemporal Based Background Subtraction (TS-BS) process at the third hidden layer, in which it effectively segments the foreground images from dynamic changing background. Then, ASSC-DNL practice deep analyzes the foreground image of video frames and mines some features like shape, color, texture, intensity, and size. Finally, ASSC-DNL Technique exactly finds the moving objects in video frames according to identified features with minimal time at the output layer. Therefore, ASSC-DNL Technique obtains enhanced moving objects detection performance when compared to existing works. The simulation of ASSC-DNL practice is conducted via different metrics such as accuracy, time and false positive rate towards in detection.

Using Multiscale Edge Detection for Low Bit-Rate Subband Video Coding

2012 ◽  
Author(s):  
Mohsen Ashourian ◽  
Zulkalnain Mohd. Yusof ◽  
Sheikh Hussain S. Salleh ◽  
Syed Abd. Rahman S. A. Bakar
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
Three Dimensional ◽  
Spatial Filter ◽  
Video Codec ◽  
Bit Rate ◽  
Low Bit Rate ◽  
Video Frames ◽  
Tele Monitoring ◽  
Efficient Selection

This paper introduces a video compression system for very low bit–rate video–conferencing and tele–monitoring applications. The video codec first performs a three–dimensional subband decomposition on a group of video frames, and then encode the subbands with different quantization methods. By using a cubic spline wavelet, the spatial filter bank acts as a multiscale edge detector. This property is used for efficient selection and coding of high frequency subbands with geometric vector quantization. For lowest tempo–spatial subband, a DPCM coding with an entropy coder was used. Results at several low bit rates (16,32, 64, 128 Kbps) are reported and compared with H.263, the standard for low bit rate video coding.

scholarly journals Deceptive Techniques to Hide a Compressed Video Stream for Information Security

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7200
Author(s):  
Jeonghwan Heo ◽  
Jechang Jeong
Keyword(s):  
Information Security ◽  
Video Compression ◽  
Video Transmission ◽  
Video Stream ◽  
Test Signal ◽  
Video Codec ◽  
Compressed Video ◽  
Video Distribution ◽  
Iot Devices ◽  
Encryption Method

With the recent development of video compression methods, video transmission on traditional devices and video distribution using networks has increased in various devices such as drones, IP cameras, and small IoT devices. As a result, the demand for encryption techniques such as MPEG-DASH for transmitting streams over networks is increasing. These video stream security methods guarantee stream confidentiality. However, they do not hide the fact that the encrypted stream is being transmitted over the network. Considering that sniffing attacks can analyze the entropy of the stream and scan huge amounts of traffic on the network, to solve this problem, the deception method is required, which appears unencrypted but a confidential stream. In this paper, we propose the new deception method that utilizes standard NAL unit rules of video codec, where the unpromised device shows the cover video and the promised device shows the secret video for deceptive security. This method allows a low encryption cost and the stream to dodge entropy-based sniffing scan attacks. The proposed stream shows that successful decoding using five standard decoders and processing performance was 61% faster than the conventional encryption method in the test signal conformance set. In addition, a network encrypted stream scan method the HEDGE showed classification results that our stream is similar to a compressed video.

scholarly journals DWT Based-Video Compression Using (4SS) Matching Algorithm

2015 ◽  
Vol 1 (4) ◽  
pp. 427
Author(s):  
Marwa Kamel Hussien ◽  
Hameed Abdul-Kareem Younis
Keyword(s):  
Video Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Motion Vector ◽  
Transmission Efficiency ◽  
Video Encoding ◽  
Discrete Wavelet ◽  
Still Image ◽  
Huffman Encoding ◽  
Good Trade

Currently, multimedia technology is widely used. Using the video encoding compression technology can save storage space, and also can improve the transmission efficiency of network communications. In video compression methods, the first frame of video is independently compressed as a still image, this is called intra coded frame. The remaining successive frames are compressed by estimating the disparity between two adjacent frames, which is called inter coded frame. In this paper, Discrete Wavelet Transform (DWT) is used powerful tool in video compression. Our coder achieves a good trade-off between compression ratio and quality of the reconstructed video. The motion estimation and compensation, which is an essential part in the compression, is based on segment movements. The disparity between each two frames was estimated by Four Step Search (4SS) Algorithm. The result of the Motion Vector (MV) was encoded into a bit stream by Huffman encoding while the remaining part is compressed like the compression was used in intra frame. Experimental results showed good results in terms of Peak Signal-to-Noise Ratio (PSNR), Compression Ratio (CR), and processing time.

Pyramid Vector Quantization of Video Subband With Dithering

2012 ◽  
Author(s):  
Mohsen Ashourian ◽  
Zulkalnain Mohd. Yusof ◽  
Sheikh Hussain S. Salleh ◽  
Syed Abd. Rahman S. A. Bakar
Keyword(s):  
Video Compression ◽  
Vector Quantization ◽  
Three Dimensional ◽  
Low Complexity ◽  
Video Codec ◽  
Subjective Test ◽  
Compression Scheme ◽  
Fixed Rate ◽  
Video Signals ◽  
Video Frames

This paper describes the development of a low complexity and fixed–rate video compression scheme based on three–dimensional subband coding of video signals. The video codec first performs three–dimensional subband decomposition on a group of video frames, and then encode high frequency subbands with pyramid vector quantization and lowest tempo–spatial band with a DPCM coding in time and space. To improve the visual quality of reconstructed video, different types of subtractive and non–subtractive dithering of pyramid vector quantizers were experimented and its effectiveness was proved by a standard pair comparison subjective test. Coder complexity was reduced by using longer filters in the first level of spatial decomposition for better selectivity and coding gain and shorter filter in the second level of decomposition for lower complexity. Results at different low bit–rate (64, 128 and 384 Kbps) for several standard video sequences are reported and compared with ITU standard H.263.

COMPUTATIONAL AND EXPERIMENTAL STUDIES OF A LOW-EMISSION BURNER FOR A PERSPECTIVE TURBOJET ENGINE WITH THE COMPRESSION RATIO EXCEEDING 40

2020 ◽  
Author(s):  
M. A. Danilov ◽  
◽  
M. V. Drobysh ◽  
A. N. Dubovitsky ◽  
F. G. Markov ◽  
...  
Keyword(s):  
Compression Ratio ◽  
Experimental Studies ◽  
The Other ◽  
Aircraft Engines ◽  
Engine Efficiency ◽  
Other Hand ◽  
Turbojet Engine ◽  
Low Emission ◽  
Civil Aircraft ◽  
The One

Restrictions of emissions for civil aircraft engines, on the one hand, and the need in increasing the engine efficiency, on the other hand, cause difficulties during development of low-emission combustors for such engines.

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