Perceptual image compression for data transmission on the battlefield

1998 ◽  
Author(s):  
Jose G. Gonzalez ◽  
Mark J. T. Smith ◽  
Ingo Hontsch ◽  
Lina J. Karam ◽  
Kameswara R. Namuduri ◽  
...  
Keyword(s):  
Image Compression ◽  
Data Transmission ◽  
Perceptual Image Compression

scholarly journals Remote Video Surveillance System Based on Direct Show and Image Compression

2013 ◽  
Vol 756-759 ◽  
pp. 439-442
Author(s):  
Shang Fu Gong ◽  
Li Gang Wu ◽  
Yan Jun Wang
Keyword(s):  
Image Compression ◽  
Real Time ◽  
Video Surveillance ◽  
Data Transmission ◽  
Video Transmission ◽  
Massive Data ◽  
Time Requirements ◽  
Rich Information ◽  
Precautionary Measures ◽  
Application Requirements

Video surveillance, convenience and rich information, has been widely used in security, protection, monitoring and other occasions, and has already been one of the most important precautionary measures in commercial, residential and transportation areas. However, considering the massive data transmission needs and higher real-time requirements for video surveillance, a remote video surveillance plan has been put forward on the analysis basis of Microsoft DirectShow and Image Compression. This plan adopts the C/S structure, adapts to the requirements of real-time video transmission, with a better fluency. In addition, the picture clarity satisfies the application requirements.

scholarly journals Image compression based on classification coding of constant-pitched functions transformers

2021 ◽  
pp. 48-62
Author(s):  
Vladimir Barannik ◽  
Andrii Krasnorutsky ◽  
Sergii Shulgin ◽  
Valerii Yeroshenko ◽  
Yevhenii Sidchenko ◽  
...  
Keyword(s):  
Image Compression ◽  
Data Transmission ◽  
High Frequency ◽  
Orthogonal Transformation ◽  
Low Frequency ◽  
Information Delivery ◽  
Video Data ◽  
Arithmetic Coding ◽  
Video Images ◽  
Frequency Components

The subject of research in the article are the processes of video image processing using an orthogonal transformation for data transmission in information and telecommunication networks. The aim is to build a method of compression of video images while maintaining the efficiency of its delivery at a given informative probability. That will allow to provide a gain in the time of delivery of compressed video images, a necessary level of availability and authenticity at transfer of video data with preservation of strictly statistical regulations and the controlled loss of quality. Task: to study the known algorithms for selective processing of static video at the stage of approximation and statistical coding of the data based on JPEG-platform. The methods used are algorithm based on JPEG-platform, methods of approximation by orthogonal transformation of information blocks, arithmetic coding. It is a solution of scientific task-developed methods for reducing the computational complexity of transformations (compression and decompression) of static video images in the equipment for processing visual information signals, which will increase the efficiency of information delivery.The following results were obtained. The method of video image compression with preservation of the efficiency of its delivery at the set informative probability is developed. That will allow to fulfill the set requirements at the preservation of structural-statistical economy, providing a gain in time to bring compressed images based on the developed method, relative to known methods, on average up to 2 times. This gain is because with a slight difference in the compression ratio of highly saturated images compared to the JPEG-2000 method, for the developed method, the processing time will be less by at least 34%.Moreover, with the increase in the volume of transmitted images and the data transmission speed in the communication channel - the gain in the time of delivery for the developed method will increase. Here, the loss of quality of the compressed/restored image does not exceed 2% by RMS, or not worse than 45 dB by PSNR. What is unnoticeable to the human eye.Conclusions. The scientific novelty of the obtained results is as follows: for the first time the method of classification (separate) coding (compression) of high-frequency and low-frequency components of Walsh transformants of video images is offered and investigated, which allows to consider their different dynamic range and statistical redundancy reduced using arithmetic coding. This method will allow to ensure the necessary level of availability and authenticity when transmitting video data, while maintaining strict statistical statistics.Note that the proposed method fulfills the set tasks to increase the efficiency of information delivery. Simultaneously, the method for reducing the time complexity of the conversion of highly saturated video images using their representation by the transformants of the discrete Walsh transformation was further developed. It is substantiated that the perspective direction of improvement of methods of image compression is the application of orthogonal transformations on the basis of integer piecewise-constant functions, and methods of integer arithmetic coding of values of transformant transformations.It is substantiated that the joint use of Walsh transformation and arithmetic coding, which reduces the time of compression and recovery of images; reduces additional statistical redundancy. To further increase the degree of compression, a classification coding of low-frequency and high-frequency components of Walsh transformants is developed. It is shown that an additional reduction in statistical redundancy in the arrays of low-frequency components of Walsh transformants is achieved due to their difference in representation. Recommendations for the parameters of the compression method for which the lowest value of the total time of information delivery is provided are substantiated.

Image Compression Technology Based on the Analysis Theory of Wavelet

2012 ◽  
Vol 160 ◽  
pp. 400-404
Author(s):  
Hui Guo ◽  
Jie He
Keyword(s):  
Image Compression ◽  
Data Transmission ◽  
Quantitative Data ◽  
Image Data ◽  
Compression Algorithm ◽  
Compression Method ◽  
Huge Amount ◽  
Analysis Theory ◽  
Wavelet Image ◽  
Image Compression Algorithm

Due to the huge amount of image data transmission conditions and the existing relative low, makes the image compression become inevitable, key technology of image compression for image data transform to transform the quantitative data, as well as to the quantitative data, after the entropy coding.And this article USES the 2 d Mallat of wavelet image compression algorithm is a kind of common image compression method of wavelet image compression algorithm is the core.

Application of Steganography for Secure Data Transmission Using Lossless Compression

2021 ◽  
pp. 279-305
Author(s):  
Kylyn Fernandes ◽  
Ankit Rishi Gupta ◽  
Pratik Panchal ◽  
Ramchandra Mangrulkar
Keyword(s):  
Social Media ◽  
Image Compression ◽  
Data Transmission ◽  
Lossless Compression ◽  
Use Case ◽  
Physical Methods ◽  
Digital Era ◽  
Secure Data ◽  
Secure Data Transmission ◽  
Image Transformations

Steganography is the art of hiding messages or files in a way that prevents the detection of the existence of these hidden messages. It encompasses several techniques, including physical methods like invisible ink on paper and digital techniques like hiding text on multimedia files like images and music files. In the modern digital era, steganography has become a useful tool to evade detection and perusal of secret messages. With the advent of social media, it is very easy to encode a message or file onto an image and upload it online for the intended recipients to access, decode, and read or use. In this case of digital steganography of messages or files onto images, an important factor to consider is the effect of image compression on the hidden message. Since most social media and other online image posting websites run some sort of compression, cropping, and other image transformations on the uploaded images, understanding these techniques and their effect on the hidden text can help one choose the most suitable steganography technique to use for a particular use case.

scholarly journals Dictionary based Image Compression via Sparse Representation

2017 ◽  
Vol 7 (4) ◽  
pp. 1964 ◽  
Author(s):  
Arabinda Sahoo ◽  
Pranati Das
Keyword(s):  
Image Quality ◽  
Image Compression ◽  
Sparse Representation ◽  
Data Transmission ◽  
State Of The Art ◽  
Experimental Result ◽  
Storage Space ◽  
Image Block ◽  
Current Image ◽  
Coding Efficiency

Nowadays image compression has become a necessity due to a large volume of images. For efficient use of storage space and data transmission, it becomes essential to compress the image. In this paper, we propose a dictionary based image compression framework via sparse representation, with the construction of a trained over-complete dictionary. The over-complete dictionary is trained using the intra-prediction residuals obtained from different images and is applied for sparse representation. In this method, the current image block is first predicted from its spatially neighboring blocks, and then the prediction residuals are encoded via sparse representation. Sparse approximation algorithm and the trained over-complete dictionary are applied for sparse representation of prediction residuals. The detail coefficients obtained from sparse representation are used for encoding. Experimental result shows that the proposed method yields both improved coding efficiency and image quality as compared to some state-of-the-art image compression methods.

scholarly journals Fuzzy logic and image compression based energy efficient application layer algorithm for wireless multimedia sensor networks

2020 ◽  
Vol 17 (2) ◽  
pp. 509-536
Author(s):  
Arafat Senturk ◽  
Resul Kara ◽  
Ibrahim Ozcelik
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Data Transmission ◽  
Wireless Multimedia Sensor Networks ◽  
Environmental Data ◽  
Sensor Nodes ◽  
Wireless Multimedia ◽  
Application Layer ◽  
Multimedia Sensor Networks

Wireless Sensor Networks (WSN) are the networks that can realize data processing and computation skills of sensor nodes over the wireless channel and they have several communication devices. Wireless Multimedia Sensor Networks (WMSN) are the networks composed of low-cost sensor nodes that transmit realtime multimedia data like voice, image, and video to each other and to sink. WMSN needs more energy and bandwidth than WSN since they transmit a larger amount of data. The size of the data transmitted by the sensor nodes to each other or the sink becomes an important factor in their energy consumption. Energy consumption is a fundamental issue for WMSN. Other issues that affect the progress of WMSN are limited bandwidth and memory constraints. In these networks, for which the node battery lives are important sources, the limited sources must be effectively used by decreasing the transmitted data amount by removing the redundant data after proper processing of the environmental data. A new algorithm is developed to minimize the energy consumption during image data transmission between sensor nodes on WMSN, and so, make the nodes use their most important source, battery life effectively in this study. This algorithm is named as Energy-aware Application Layer Algorithm based on Image Compression (EALAIC). This algorithm makes use of the top three image compression algorithms for WMSN and decides instantly to which one is the most efficient based on three parameters: the distance between the nodes, total node number, and data transmission frequency. In this way, the sensor node battery lives are used efficiently. The performance analysis of the developed algorithm is also done via Network Simulator ? 2 (NS ? 2) and it is compared by the existing algorithms in terms of energy rate (consumed energy/total energy) and PSNR (Peak Signal to Noise Ratio).

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