Hardware Design of Video Compression System Based on TMS320DM368

Usually, it is difficult to perform compression in video files as it significantly affects the perceptible quality. This paper has reviewed various works of literature toward finding unique approaches to video compression to find that the existing techniques offer a sophisticated algorithm for implementation with less focus on the visual quality of the decoded contents. Hence, this paper presents a model that uses graph theory to perform video compression compatible with High-Efficiency Video Coding (HEVC) standards of compression. By adoption of the Lagrangian theorem, the proposed algorithm finds the best solution for compression and offers better compression standards. The outcomes are compared with existing H.264 and existing research work to find that the proposed system excels better with respect to PSNR and bit rate and thereby offers better compatibility to compress High Definition (HD) videos.

Efficient content-based search and retrieval of video databases has become an important industrial and consumer application due to rapid proliferation of compressed digital video data on the Internet and corporate Intranets, and due to the launch of high definition television (HDTV) broadcasts in 1998. We have developed the first HDTV video content management system that automatically analyzes motion occurring in MPEG-2 encoded videos within the compressed domain itself. Our system produces descriptors characterizing the global motion in videos for content retrieval and repurposing applications in a digital television studio. These motion-direction and magnitude based video labels can be directly, incorporated as annotation indexes into a database for querying, or used to construct higher level event descriptions of videos. Results from our ongoing experiments with tens of thousands of frames obtained from several MPEG-1,2 video streams of various genres demonstrate the good performance of our annotation system in terms of motion identification accuracy and computational efficiency.

The subject of study. A new algorithm for real-time data compression in a video surveillance system from an unmanned aerial vehicle is proposed. The algorithm makes it possible to obtain different degrees of video data compression using different codecs for specific video recording conditions (UAV altitude and flight speed, nature of the observed terrain, etc.), and also provides the ability to transmit video data to the flight control point via radio channel. A detailed analysis of the quality of the proposed algorithm for shooting in various video formats that meet international standards (HD and Full HD) was carried out, both in terms of visual perception and objective criteria. The purpose of the study was to conduct a comprehensive research on the problem of improving the quality of the video surveillance system from the UAV and to create a video compression algorithm that allows broadcasting video data to the control center in real time with high quality. Objectives. To develop and programmatically implement a video compression algorithm based on modern codecs for video surveillance sys­tems on board a UAV. To use modern video cameras and a microcomputer platform as hardware. To analyze the quality indicators of the algorithm in different conditions. Methods used. Evaluation of visual perception of video compression results, statistical analysis and processing of the parameters of the analyzed video sequence as a random spatio-temporal process. Results. A new video data compression algorithm for the UAV video surveillance system based on the Raspberry Pi 5 microcomputer using modern video compression codecs H.264 and H.265 was synthesized. The algorithm provides the required compression ratio and data transmission rate over the radio channel between the UAV and the flight control center. Detailed estimates of the quality of the algorithm are obtained. Conclusions. Scientific novelty of the results: A new universal video data compression algorithm for video surveillance systems on board UAVs with the ability to transmit video over a radio channel in real time has been proposed and implemented. The quality of the proposed algorithm is verified on real video surveillance results. The proposed algorithm is implemented in the Python software environment.

compressed domain processing, transcoding, video editing, MPEG, splicing, reverse play, frame rate conversion, interlace to progressive, motion vector resampling Video compression algorithms are being used to compress digital video for a wide variety of applications, including video delivery over the Internet, advanced television broadcasting, video streaming, video conferencing, and video storage and editing. The impressive performance of modern compression algorithms, combined with the growing availability of video encoders and decoders and low-cost computers, storage devices, and networking equipment, makes it evident that between video capture and video playback, video will be handled in compressed video form. The resulting end-toend compressed digital video systems motivate the need to develop efficient algorithms for handling compressed digital video.

Efficient detection of organic pollutants is important for environmental monitoring, food safety and industrial pollution control. Although traditional organic pollutant detection instruments have high detection accuracy, the long detection period and high detection cost make it difficult to meet the demand of real-time monitoring. To address this problem, this study proposes an organic pollutant detection device based on STM32. The device uses fluorescence spectroscopy to detect its organic pollutants, taking benzene, toluene and xylene as the research objects, adopting the principle of spectral feature recognition, and through the combination of sensor design and chemical analysis experiments, designing a multi-channel water quality detection sensor suitable for quantitative detection of the three benzene species to achieve the specific identification of the target pollutants in the water body. Compared with the traditional single-spectrum detection method, the system has obvious advantages in terms of pollutant recognition rate, detection speed and portability. This study provides a new design idea for on-site real-time detection and environmental pollution monitoring, which has important practical application value.

In this paper, a video compression standard used in digital television systems is discussed. Basic concepts of video compression and principles of lossy and lossless compression are given. Techniques of video compression (intraframe and interframe compression), the type of frames and principles of the bit rate compression are discussed. Characteristics of standard-definition television (SDTV), high-definition television (HDTV) and ultra-high-definition television (UHDTV) are given. The principles of the MPEG-2, MPEG-4 and High Efficiency Video Coding (HEVC) compression standards are analyzed. Overview of basic standards of video compression and the impact of compression on the quality of TV images and the number of TV channels in the multiplexes of terrestrial and satellite digital TV transmission are shown. This work is divided into six sections.

Real-time video image processing requires video compression techniques. Efficient Motion Estimation (ME) and Motion Compensation (MC) algorithms and their successful hardware implementation are the key to video compression. Work on developing and implementing efficient ME and MC algorithms for multi-camera systems is ongoing. The low power consumption yet high speed of Heterogeneous Reconfigurable Devices such as Field Programmable Gate Arrays (FPGA) can be suitable for implementation of real-time optic flow computation using multi-camera systems. This paper focuses on a search into the current state-of-the-art for multi-camera motion tracking. It has been found the tracking systems mainly focused on people and vehicle tracking in both indoor and outdoor conditions, tracking under occlusion, tracking for surveillance, single and multi-view tracking, etc. The review search also found use of multi-camera tracking in the medical sector, such as multi-camera tracking systems for respiratory motion tracking. Research on this field has not been explored much and this holds possibilities for further work.

Performance Evaluation of Video Compression Using Different Wavelets and Tensors for Multimedia Applications

Video compression uses encoding to convert video files into smaller files for efficient storage and transmission in image processing. A decoder reconstructs the received data into a representation of the original video. This research presents recently added in-loop as a filtering technique for extension of sample adaptive offset (SAO) in High-Efficiency Video Coding (HEVC).The principle of SAO is to lessen pixel errors caused by the compression process. Through this an average data reduction up to 1.43% in Low delay configuration and 1.03% in Random access configuration

Embedded video surveillance has become a large market as the number of installed cameras around us can show. At the same time, video compression technique has been rapidly developed in recent years. As a new generation of video coding compression standard, extensive attention has been given to H.264/AVC. On the other hand, because of good cost-effective and low-power consumption, DSP is widely used in the fields of embedded system and multimedia processing. There are needs for embedded video surveillance that can make use of the video compression technique in more efficiency security systems. In this paper, a scheme of design and implementation about video surveillance system based on H.264/AVC is designed and described. It is built on ADSP-BF561, with a wide range of peripheral interface, to achieve several functions, such as video compression, data stream control, network transmission, PTZ and so on. The experimental results indicate that the stability and other expected features of system, including Real-time surveillance video encoding, can be ensured.

An active 2.45 GHz RFID system based on C8051F3XX series MCU and nRF24L01 low power radio transceiver chip is introduced in this article with emphasis on the system's hardware design, realization scheme of anti-collision algorithm (combined with the principle of power control technology) ,safety solution and realization of label's low power consumption. This active RFID system designed in this article can be used as automatic identification remotely for containers in the environment of the terminals, as well as the system for remote identification and control such as in the information collection and control for the vehicle transit and the toll gate in the case of vehicle non-stopping.

Today, in a multimedia age, electronic displays are the essential key devices involved in the relation between multimedia equipment and human beings. Flat panel displays are overcoming the restrictions of traditional CRTs (Cathode Ray Tubes) regarding portability and large screen capability, and they are ready to expand their multimedia application fields. TFT-LCDs (Thin Film Transistor-Liquid Crystal Displays) in particular have advantages such as light weight, low profile, low power consumption, and motion picture display, and importantly contribute the development of multimedia. The color PDP (Plasma Display Panel) features emissive display, a large screen, and a low profile, and mass production aimed at implementing space-saving, and wall-hung HDTV (High Definition Television) is about to be started. Since further development of multimedia is expected in the twenty-first century, the scale of this market is immeasurable. At the same time, the flat panel display market will also expand. Wide variety of flat panel displays will gain wider use as they secure their respective markets through their particular advantages.KeywordsMultimediaDevice technologyElectronic displayFlat panel displayLCDTFT-LCDColor PDP

Abstract-the paper introduced a kind of intrinsic safety multifunction data processing terminal used in underground based on microprocessor chip S3C6410. It can record the underground multifunction data under the environment of whole dark (0Lux) through night-vision device, headphone, microphone etc, and achieve the multifunction frequency data's wireless transmission and wire transmission through WiFi (Wireless Fidelity), USB technology. The low-voltage (≤3.3V) design of the system power both in conformity with the intrinsically safe demands and realize the low power consumption (3.5W) of the device. The software of the data processing terminal uses Windows CE as the platform of the embedded operating system. Especially it can be well used on mine security, saving and emergent area, having higher applied value. The experiments show that the underground multimedia data processing terminal based on ARM11 can realize the high definition display, the collection, processing, displaying, storing and transmitting of the audio data.

In this study, we present the design and development of a mobile, multi-modal electroencephalography and functional near-infrared spectroscopy (EEG/fNIRS) device for wireless neurophysiological monitoring. The system was engineered to achieve high signal fidelity, low power consumption, and a fully untethered operation suitable for ambulatory brain research. The device integrates four Texas Instruments ADS1299 24-bit biopotential amplifiers, providing up to 32 simultaneous acquisition channels. Signal control, processing, and local storage via an SD card are managed by an STM32H7 microcontroller, while an ESP32-S2 module handles Wi-Fi communication. Dual-wavelength light-emitting diodes and OPT101 photodiodes form the optical front-end, driven by digitally controlled constant-current sources for stable illumination. The design employs galvanic isolation, multi-rail power management, and a four-layer PCB layout to minimise interference between analogue, power, and digital domains. Data are captured by a deterministic, clock-driven STM32 acquisition loop and forwarded to the ESP32, which operates under an RTOS and streams packets over Wi-Fi for collection on a mobile phone or PC using the Lab Streaming Layer (LSL) framework. The STM32H7 architecture was chosen for its capability to support future embedded edge-machine-learning functions, enabling on-device signal quality assessment and artefact rejection. Validation demonstrations include 32-channel synchronised acquisition using the ADS1299 internal test signal, eyes-open/eyes-closed alpha modulation visualised in EEGLAB, a forehead fNIRS breath-hold response with physiological spectral content, and real-time ECG/optical pulse streaming via LSL. The resulting system provides a compact platform with explicitly defined acquisition and data interfaces for synchronised EEG/fNIRS acquisition, enabling scalable, low-cost mobile neuroimaging research.

Video compression is achieved in the spectrum-compatible high-definition television (SC-HDTV) system by adaptive transform subband coding. The number of subbands is significantly increased, and the temporal processing is greatly reduced. Coefficients are transmitted as analog data; side information representing adaptation is transmitted as part of the digital data signal.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>