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A wireless image transmission system is proposed, which in order to offset the disadvantages of wire video monitor laying points hard, and disadvantages of wire video monitor implementing hard in bad circumstance. The core of the system is TI series of C5000 high speed DSP processor and radio frequency wireless communication chip. Through DSP transplantation of JPEG compression algorithm, complete image collection and image compression through DSP, use wireless receiving and sending module to complete wireless images data transmission. Use wireless receiving and sending module instead of emitter and network as image data transmission device, low cost, not required network fee, system can real-time complete terminal images collection and show. It can apply community guard and video monitor of deploying points urgently in the electric power system, factory, bank and other important department, which dont require higher performance.
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García, J. A., Rosa Rodriguez-Sánchez, and J. Fdez-Valdivia. "Sustainable image transmission." Journal of Visual Communication and Image Representation 23, no. 1 (January 2012): 134–42. http://dx.doi.org/10.1016/j.jvcir.2011.09.004.
Wei Gong, K. R. Rao, and M. T. Manry. "Progressive image transmission." IEEE Transactions on Circuits and Systems for Video Technology 3, no. 5 (1993): 380–83. http://dx.doi.org/10.1109/76.246089.
Nivedita, S. Angelin, and Dr T. Priyaradhikadevi. "Image Realization Steganography by Secure Key Transmission." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (February 28, 2018): 1460–64. http://dx.doi.org/10.31142/ijtsrd9654.
Chen, Yuanming, Xiaobin Hong, Bin Cui, and Rongfa Peng. "Implementation of an Efficient Image Transmission Algorithm for Unmanned Surface Vehicles Based on Semantic Communication." Journal of Marine Science and Engineering 11, no. 12 (November 30, 2023): 2280. http://dx.doi.org/10.3390/jmse11122280.
With the increasingly maturing technology of unmanned surface vehicles (USVs), their applications are becoming more and more widespread. In order to meet operational requirements in complex scenarios, the real-time interaction and linkage of a large amount of information is required between USVs, between USVs and mother ships, and between USVs and shore-based monitoring systems. Visual images are the main perceptual information gathered from USVs, and their efficient transmission and recognition directly affect the real-time performance of information exchange. However, poor maritime communication signals, strong channel interference, and low bandwidth pose great challenges to efficient image transmission. Traditional image transmission methods have difficulty meeting the real-time and image quality requirements of visual image transmissions from USVs. Therefore, this paper proposes an efficient method for visual image transmission from USVs based on semantic communication. A self-encoder network for semantic encoding which compresses the image into low-dimensional latent semantics through the encoding end, thereby preserving semantic information while greatly reducing the amount of data transmitted, is designed. On the other hand, a generative adversarial network is designed for semantic decoding. The decoding end decodes and reconstructs high-quality images from the semantic information transmitted through the channel, thereby improving the efficiency of image transmission. The experimental results show that the performance of the algorithm is significantly superior to traditional image transmission methods, achieving the best image quality while transmitting the minimum amount of data. Compared with the typical BPG algorithm, when the compression ratio of the proposed algorithm is 51.6% of that of the BPG algorithm, the PSNR and SSIM values are 7.6% and 5.7% higher than the BPG algorithm, respectively. And the average total time of the proposed algorithm is only 59.4% of that of the BPG algorithm.
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Yang, Ying, Xingchuang Xiong, Zilong Liu, Shangzhong Jin, and Juan Wang. "High-Performance Encryption Algorithms for Dynamic Images Transmission." Electronics 13, no. 1 (December 28, 2023): 131. http://dx.doi.org/10.3390/electronics13010131.
With the proliferation of the internet, the issue of image tampering has escalated, necessitating robust image encryption schemes. Despite the multitude of proposed image encryption algorithms, challenges such as slow computational speed, weak security, and suboptimal visibility persist. This study addresses these challenges by introducing a high-performance encryption algorithm tailored for dynamic images—QEDI (Quick Encryption Algorithm for Dynamic Images). QEDI leverages elliptic curve-based asymmetric encryption algorithms and hash algorithms. The process involves using a hash algorithm to calculate the hash of the dynamic image slated for encryption, employing the elliptic curve algorithm to generate public and private keys, and utilizing the asymmetric encryption algorithm to process the image hash, resulting in a signature ciphertext. This ciphertext is embedded into the dynamic image, completing the encryption process. To enhance the execution speed without compromising the image quality and visibility, the bit depth of the dynamic image is reduced before hash calculation, and custom information fields are encapsulated to embed the signature ciphertext into the dynamic image. Experimental evaluations, conducted within a dynamic image generation system, encompassed assessments of security, encryption algorithm execution time, and image quality. The results indicate that utilizing QEDI for dynamic image encryption yields better security compared to EDI (Encryption Algorithm for Dynamic Images). QEDI exhibits minimal impact on image quality, with a noteworthy 69.77% reduction in execution time compared to EDI. Furthermore, when compared to existing algorithms employing image conversion for encryption, QEDI-encrypted images demonstrate enhanced visibility, better image quality, and expedited encryption speed.
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Adeyinka, Michael. "Telepathological (Image Transmission) Configuration." Journal of Telemedicine and Telecare 2, no. 1_suppl (June 1996): 21–24. http://dx.doi.org/10.1177/1357633x9600201s07.
The Laboratory for Biomedical Informatics (LBMI) has developed a digital microscope control module incorporated into an image analysis system. This is now equipped with an ISDN switch box for linking up with a remote computer-based station for delivering histopathological services. The FRAME, client/server integrated software, was developed to initiate the communication link, adjust the microscope settings, acquire and transmit images. This LBMI telepathology initiative employs simple solutions to arrive at the point of prototyping and demonstrating the state of the art on the one hand and encountering the prevailing problems in order to deliberate on possible remedies on the other.
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CHANG, CHING-YUN, and IUON-CHANG LIN. "AN EFFICIENT PROGRESSIVE IMAGE TRANSMISSION SCHEME FOR CHINESE CALLIGRAPHY." International Journal of Pattern Recognition and Artificial Intelligence 20, no. 07 (November 2006): 1077–92. http://dx.doi.org/10.1142/s0218001406005083.
We invented a progressive image transmission scheme that is used for transmitting Chinese calligraphy. The scheme employs the property of simple colors of calligraphy images to design a method of transmitting images phase by phase. Overall, our scheme can achieve the following two goals. One is compressing the image data to reduce the transmission time while the other is gaining less response time by using progressive image transmission. Furthermore, the recovered image still maintains the colors of the seals with high image quality.
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Rizal, Syamsul, and Dong-Seong Kim. "Image Transmission in Military Network Using Bézier Curve." Journal of Advances in Computer Networks 3, no. 2 (2015): 141–45. http://dx.doi.org/10.7763/jacn.2015.v3.156.
Shoydin, Sergey A., and Artem L. Pazoev. "«Uncanny valley» effect in holographic image transmission." Journal of the Belarusian State University. Physics, no. 3 (October 20, 2022): 4–9. http://dx.doi.org/10.33581/2520-2243-2022-3-4-9.
The quality of computer-synthesised images is continuously improving, increasing in the volume of files representing them. It is noticed that passing from simple schematic images to increasingly complex ones, their perception goes through different stages. If initially the complication of the image and its approximation to the real image of a person makes a favourable impression, then there comes a moment of fright and rejection. Masahiro Mori called it the «uncanny valley» effect. Since then, all new technologies for presenting human images have been tested in order to avoid this effect. This effect should be treated especially carefully when compressing and then restoring complex images. This paper shows the position relative to the «uncanny valley» of the reconstructed 3D images, reconstructed by a hologram synthesised and transmitted with compression over the communication channel in accordance with patent RU2707582C1.
Salous, Mounther N. H. "Context-based image transmission." Thesis, University of Birmingham, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368121.
Lim, Seng. "Image compression scheme for network transmission." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA294959.
Local Area Networks (LAN) are destined to play a rapidly increasing part in the transmission and distribution of a wide range of information, and this thesis describes the study of the problems concerning the transmission of coloured images over a particu1ar network, the Cambridge Ring. A colour image station has been developed for the use on the Cambridge Ring. It provides two main services: a high resolution freeze frame transmission and a medium resolution slow-scan image transmission.
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Iyengar, Giridharan. "Algorithms and architectures for progressive image transmission." Thesis, University of Ottawa (Canada), 1993. http://hdl.handle.net/10393/6747.
Transmission of images over low speed, low bandwidth channels has several applications. Examples include transmission of remote sensing images, scanning of vast global databases and facsimile transmission of printed material. In progressive image transmission, a low resolution image is first transmitted with as few bits as possible. The resolution of the transmitted image is then improved interactively upon viewer's request. Eventually, an exact copy of the original image is reconstructed. In this thesis, image coding techniques and parallel architectures are first reviewed followed by a review of progressive image transmission techniques. A software toolkit for progressive image transmission is then presented. This tool is user-friendly and permits rapid development of new algorithms and fast evaluations of different approaches for progressive image transmission. Unlike conventional techniques, it offers a convenient platform for performing both objective and subjective evaluations with ease. Two algorithms for progressive image transmission are then detailed. The first algorithm follows the coefficient scanning methodology. The second algorithm uses an iterative residual error feedback technique. An architecture which implements these algorithms in real-time is then presented. The software tool is used as the platform with which the comparative analysis between different algorithms are performed. Simulation results are reported for the proposed algorithms in terms of Peak Signal to Noise Ratio (PSNR). Simulation results indicate that the proposed algorithms perform better than JPEG-DCT in terms of subjective and objective quality. However, Gabor decomposition is computationally expensive and hence requires special purpose architectures for real-time implementation. The proposed architecture achieves a high efficiency of parallelism (99%) and implements the two algorithms for progressive image transmission in real-time. The architecture is simple and modular and hence can be easily implemented in VLSI as a codec.
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Caron, Steven. "Progressive image transmission by segmentation-based coding." Thesis, University of Ottawa (Canada), 1996. http://hdl.handle.net/10393/9933.
Progressive image transmission, where an image builds up gradually, is gaining popularity in image database browsing applications. In these applications, a user might have to reject a large number of unwanted images before selecting the desired one. In such a case, the time required to identify the image contents becomes very important. In this thesis, we present a novel progressive image transmission technique based on a representation by segmentation. The technique preserves edges at low bit rates and is biased toward fast identification. An image is segmented into regions having constant intensity by applying a morphological operator: the watershed. The segmented image is gradually simplified using a graph. The simplifications are transmitted in the reverse order. At the decoder, the image is dynamically divided into an increasing number of regions as the transmission progresses. A subjective experiment was designed, and the recognition times of images transmitted with the proposed algorithm were compared with the recognition times of the same images transmitted with JPEG. The proposed method was found to result in faster recognition of image contents for almost all the images. Some work on the objective evaluation of coarse images is also presented.
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Khire, Sourabh Mohan. "Time-sensitive communication of digital images, with applications in telepathology." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29761.
Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010. Committee Chair: Jayant, Nikil; Committee Member: Anderson, David; Committee Member: Lee, Chin-Hui. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Wu, Zhi Qing. "Developing image enhancement and image transmission techniques for an Internet-oriented medical image processing system." Thesis, University of South Wales, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.411625.
inc, International Resource Development, ed. Image processing & transmission for personal computers. Norwalk, Conn., U.S.A. (6 Prowitt St., Norwalk 06855): International Resources Development Inc., 1985.
Weik, Martin H. "image transmission." In Computer Science and Communications Dictionary, 753. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_8668.
Williams, David B., and C. Barry Carter. "Image Simulation." In Transmission Electron Microscopy, 533–48. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-76501-3_30.
Williams, David B., and C. Barry Carter. "Image Simulation." In Transmission Electron Microscopy, 483–98. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-2519-3_29.
Zeng, Gengsheng Lawrence. "Transmission and Emission Tomography." In Medical Image Reconstruction, 67–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-05368-9_4.
Zhang, David, Xiaobo Li, and Zhiyong Liu. "Image Restoration from Internet Transmission Corruption." In Data Management and Internet Computing for Image/Pattern Analysis, 317–29. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1527-2_15.
Blaivas, Michael. "Ultrasound Image Transmission via Camera Phones." In Teleradiology, 89–100. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78871-3_9.
Conference papers on the topic "Image transmission":
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Blaine, G. James, Rexford L. Hill, Allen P. Rueter, Evren Senol, and James W. Studt. "Image Transmission Studies." In Medical Imaging II, edited by Roger H. Schneider and Samuel J. Dwyer III. SPIE, 1988. http://dx.doi.org/10.1117/12.968735.
N, Shahanaz, and Greeshma R. "Secret Image Transmission Through Mosaic Image." In Fourth International Conference on Computer Networks & Communications. Academy & Industry Research Collaboration Center (AIRCC), 2017. http://dx.doi.org/10.5121/csit.2017.70503.
Mocenter, Michael M. "Laptop image transmission equipment." In San Diego, '91, San Diego, CA, edited by Thomas W. Augustyn and Paul A. Henkel. SPIE, 1991. http://dx.doi.org/10.1117/12.48704.
Ryan, John P., and Beacher Pearce. "Image Transmission Over Fiber." In OE/FIBERS '89, edited by Joseph Garodnick, Lynn D. Hutcheson, and David A. Kahn. SPIE, 1990. http://dx.doi.org/10.1117/12.963445.
Nebaba, Stepan, and Alexander Pak. "Patterns detection in diffraction images of transmission electron microscopy." In International Conference "Computing for Physics and Technology - CPT2020". Bryansk State Technical University, 2020. http://dx.doi.org/10.30987/conferencearticle_5fce2770518c26.23795065.
Specialized software that supports existing approaches to processing images of the crystal structure of materials for analyzing transmission electron microscopy images have a lot of different digital image processing methods, but major part of it are weakly automated. In some tasks automated algorithms of image processing have been developed, e.g. in task of estimation of the width of a layer of material from a raster image. The paper considers the problem of automated processing of diffraction images obtained by transmission electron microscopy. A number of modifications, such as Watershed algorithm, binarization and Fast Fourier Transform, are proposed for existing image processing algorithms. These modifications can help automate the processing of the diffraction pattern of a material sample from an image of transmission electron microscopy. The given examples of image processing of particular cases of diffraction patterns have shown the prospects for the development of algorithm based on combination of the proposed modifications of considered algorithms. Adaptive binarization with Watershed segmentation would be useful in automated distance estimation in transmission electron microscopy images.
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Calvo, M. L., M. Chevalier, and E. Guibelalde. "Image Transmission In A Fibroscope: Image Quality Criterion." In Cambridge Symposium-Fiber/LASE '86, edited by Abraham Katzir. SPIE, 1987. http://dx.doi.org/10.1117/12.937378.
Mort, Michael S., and Robert J. Fontana. "Reversible image compression suitable for interactive image transmission." In Medical Imaging '90, Newport Beach, 4-9 Feb 90, edited by Murray H. Loew. SPIE, 1990. http://dx.doi.org/10.1117/12.18936.
Yelleswarapu, Chandra S., and D. V. G. L. N. Rao. "Image Processing using Nonlinear Transmission." In Frontiers in Optics. Washington, D.C.: OSA, 2006. http://dx.doi.org/10.1364/fio.2006.jsua52.
Danskin, John M., Geoffrey M. Davis, and Xiyong Song. "Fast lossy Internet image transmission." In the third ACM international conference. New York, New York, USA: ACM Press, 1995. http://dx.doi.org/10.1145/217279.215287.
Tang Jiayue and Zhang Zongcheng. "Fast Internet wavelet image transmission." In Proceedings of APCC/OECC'99 - 5th Asia Pacific Conference on Communications/4th Optoelectronics and Communications Conference. IEEE, 1999. http://dx.doi.org/10.1109/apcc.1999.820407.
Pennycook, S. J., and A. R. Lupini. Image Resolution in Scanning Transmission Electron Microscopy. Office of Scientific and Technical Information (OSTI), June 2008. http://dx.doi.org/10.2172/939888.
Tai, Anthony M. Parallel Image Transmission through a Single Optical Fiber. Fort Belvoir, VA: Defense Technical Information Center, January 1986. http://dx.doi.org/10.21236/ada163809.
Riskin, Eve A., and Richard Ladner. Wavelet and Vector Quantization Image Compression for Noisy Channel Transmission. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada379065.
Chen, Zhigang. Light Control and Image Transmission Through Photonic Lattices with Engineered Coupling. Fort Belvoir, VA: Defense Technical Information Center, May 2015. http://dx.doi.org/10.21236/ad1013289.
Bloomfield, R. A., and G. R. Dobson. Image-Data Transmission Demonstration over the Tracking and Data Relay Satellite System. Fort Belvoir, VA: Defense Technical Information Center, August 1998. http://dx.doi.org/10.21236/ada352534.
Bolgert, Peter J. A Comparison of Image Quality Evaluation Techniques for Transmission X-Ray Microscopy. Office of Scientific and Technical Information (OSTI), August 2012. http://dx.doi.org/10.2172/1049731.
Rane, Shantanu D., Jeremiah Remus, and Guillermo Sapiro. Wavelet-Domain Reconstruction of Lost Blocks in Wireless Image Transmission and Packet-Switched Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada437341.
Chen, Zhigang. Equipment for Nonlinear Photonics Research - Light Control and Image Transmission in Specially-Designed Photonic. Fort Belvoir, VA: Defense Technical Information Center, March 2014. http://dx.doi.org/10.21236/ada598473.
Mahalingam, Krishnamurthy. Collaborative Research and Development. Delivery Order 0006: Transmission Electron Microscope Image Modeling and Semiconductor Heterointerface Characterization. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada463820.
Falconer, David G. L51774 Remote Sensing of Hazardous Ground Movement about Buried Gas Transmission Lines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), August 1997. http://dx.doi.org/10.55274/r0011973.
Reviews the available sensors for monitoring hazardous ground movement. Our review was limited to airborne and spaceborne sensors for access, performance, and productivity considerations. It was observed that certain ground movement is comparatively localized, e.g., earthquake faulting, while other activity may extend for thousands of kilometers, e.g., frost heave. Accordingly, we have considered two operating modes for the sensor-platform system, namely, site-by-site and continuous corridor. To determine the suitability of the candidate sensors for pipeline monitoring, we have assessed the expected performance, operational aspects, and cost of each sensor-platform combination as a function of operating mode. Finally, we have developed a business model for (1) operation of the recommended sensor systems by fee-for-service contractors; (2) analysis of the collected data by image-analysis specialists; and (3) use of the survey products by pipeline engineers.
