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Relevant bibliographies by topics / Enhanced images

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Academic literature on the topic 'Enhanced images'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Enhanced images"

1

L. Almeida, Leandro, Maria S.V. Paiva, Francisco A. Silva, and Almir O. Artero. "Super-Resolution Images Enhanced for Applications to Character Recognition." SIJ Transactions on Computer Science Engineering & its Applications (CSEA) 01, no. 03 (2013): 09–16. http://dx.doi.org/10.9756/sijcsea/v1i3/0103520101.

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said, Shaimaa A. El. "Enhanced ultrasound images denoising technique." International Journal of Biomedical Engineering and Technology 10, no. 2 (2012): 185. http://dx.doi.org/10.1504/ijbet.2012.049368.

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Rasouli, Saifollah, and Davud Hebri. "Contrast enhanced quarter-Talbot images." Journal of the Optical Society of America A 34, no. 12 (2017): 2145. http://dx.doi.org/10.1364/josaa.34.002145.

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Mahmood, Zahid, and Paul Scheunders. "Enhanced Visualization of Hyperspectral Images." IEEE Geoscience and Remote Sensing Letters 8, no. 5 (2011): 869–73. http://dx.doi.org/10.1109/lgrs.2011.2125775.

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GETTY, DAVID J., RONALD M. PICKETT, CARL J. D??ORSI, and JOHN A. SWETS. "Enhanced Interpretation of Diagnostic Images." Investigative Radiology 23, no. 4 (1988): 240–52. http://dx.doi.org/10.1097/00004424-198804000-00002.

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Jaeho Choi, Jaeho Choi, and Young-Sung Park Young-Sung Park. "Enhanced quantitative X-ray phase-contrast images using Foucault differential filters." Chinese Optics Letters 15, no. 8 (2017): 081103. http://dx.doi.org/10.3788/col201715.081103.

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Park, Jae-Sung, Dong-Choon Hwang, Dong-Hak Shin, and Eun-Soo Kim. "Resolution-enhanced 3D image correlator using computationally reconstructed integral images." Optics Communications 276, no. 1 (2007): 72–79. http://dx.doi.org/10.1016/j.optcom.2007.04.007.

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Qu, Zhi, Yaqiong Xing, and Yafei Song. "An Image Enhancement Method Based on Non-Subsampled Shearlet Transform and Directional Information Measurement." Information 9, no. 12 (2018): 308. http://dx.doi.org/10.3390/info9120308.

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Based on the advantages of a non-subsampled shearlet transform (NSST) in image processing and the characteristics of remote sensing imagery, NSST was applied to enhance blurred images. In the NSST transform domain, directional information measurement can highlight textural features of an image edge and reduce image noise. Therefore, NSST was applied to the detailed enhancement of high-frequency sub-band coefficients. Based on the characteristics of a low-frequency image, the retinex method was used to enhance low-frequency images. Then, an NSST inverse transformation was performed on the enhan

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Juneja, Mamta, and Parvinder Singh Sandhu. "Data Hiding with Enhanced LSB Steganography and Cryptography for RGB Color Images." Indian Journal of Applied Research 3, no. 5 (2011): 118–20. http://dx.doi.org/10.15373/2249555x/may2013/35.

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Kanagala, Hari Krishna, and Dr V. V. Jayarama Krishnaiah. "Enhanced Mechanism for Classification of Glaucoma Images Using Deep Learning based CNN." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10 (2019): 111–18. http://dx.doi.org/10.5373/jardcs/v11i10/20193013.

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Dissertations / Theses on the topic "Enhanced images"

1

Munechika, Curtis K. "Merging panchromatic and multispectral images for enhanced image analysis /." Online version of thesis, 1990. http://hdl.handle.net/1850/11366.

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Hayton, Paul M. "Analysis of contrast-enhanced breast MR images." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298777.

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Ju, Chen. "Edge-enhanced segmentation for SAR images." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ34190.pdf.

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Melbourne, A. "Alignment of contrast enhanced medical images." Thesis, University College London (University of London), 2009. http://discovery.ucl.ac.uk/15846/.

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The re-alignment of series of medical images in which there are multiple contrast variations is difficult. The reason for this is that the popularmeasures of image similarity used to drive the alignment procedure do not separate the influence of intensity variation due to image feature motion and intensity variation due to feature enhancement. In particular, the appearance of new structure poses problems when it has no representation in the original image. The acquisition of many images over time, such as in dynamic contrast enhanced MRI, requires that many images with different contrast be re

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Chen, Zhouye. "Reconstruction of enhanced ultrasound images from compressed measurements." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30222/document.

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L'intérêt de l'échantillonnage compressé dans l'imagerie ultrasonore a été récemment évalué largement par plusieurs équipes de recherche. Suite aux différentes configurations d'application, il a été démontré que les données RF peuvent être reconstituées à partir d'un faible nombre de mesures et / ou en utilisant un nombre réduit d'émission d'impulsions ultrasonores. Selon le modèle de l'échantillonnage compressé, la résolution des images ultrasonores reconstruites à partir des mesures compressées dépend principalement de trois aspects: la configuration d'acquisition, c.à.d. l'incohérence de la

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Du, Xiaoyun. "Enhanced Contour Description for People Detection in Images." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31804.

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People detection has been an attractive technology in computer vision. There are many useful applications in our daily life, for instance, intelligent surveillance and driver assistance system. People detection is a challenging matter as people adopt a wide range of poses, wear diverse clothes, and are visible in different kind of backgrounds with significant changes in illumination. In this thesis, some advanced techniques and powerful tools are presented in order to design a robust people detection system. First a baseline model is implemented by combining the Histogram of Oriented Gradients

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Lu, Yi Cheng. "Classifying Liver Fibrosis Stage Using Gadoxetic Acid-Enhanced MR Images." Thesis, Linköpings universitet, Institutionen för medicin och hälsa, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-162989.

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The purpose is trying to classify the Liver Fibrosis stage using Gadoxetic Acid-EnhancedMR Images. In the very beginning, a method proposed by one Korean group is being examined and trying to reproduce their result. However, the performance is not as impressive as theirs. Then, some gray-scale image feature extraction methods are used. Last but not least, the hottest method in recent years - ConvolutionNeural Network(CNN) was utilized. Finally, the performance has been evaluated in both methods. The result shows that with manual feature extraction, the Adaboost model works pretty well that AU

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Reeves, Steven Joseph. "Sea Ice Mapping Using Enhanced Resolution Advanced Scatterometer Images." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3484.

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Sea ice is of great interest due to its effect on the global climate, the Earth's ecosystem, and human activities. Microwave remote sensing has proven to be an effective way to measure many of the characteristics of sea ice. In particular, several algorithms map the daily sea ice extent using a variety of instruments. Enhanced resolution images generated from the Scatterometer Image Reconstruction (SIR) algorithm can be used to generate a high resolution ice extent map. Previous algorithms using SIR images were developed for scatterometers which are no longer operational. The Advanced Scattero

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Usta, Fatma. "Image Processing Methods for Myocardial Scar Analysis from 3D Late-Gadolinium Enhanced Cardiac Magnetic Resonance Images." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37920.

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Myocardial scar, a non-viable tissue which occurs on the myocardium due to the insufficient blood supply to the heart muscle, is one of the leading causes of life-threatening heart disorders, including arrhythmias. Analysis of myocardial scar is important for predicting the risk of arrhythmia and locations of re-entrant circuits in patients’ hearts. For applications, such as computational modeling of cardiac electrophysiology aimed at stratifying patient risk for post-infarction arrhythmias, reconstruction of the intact geometry of scar is required. Currently, 2D multi-slice late gadolinium-e

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Tanner, Christine. "Registration and lesion classification of contrast-enhanced magnetic resonance breast images." Thesis, King's College London (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427950.

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Books on the topic "Enhanced images"

1

Judith, Watts, ed. The art of enhanced photography: Beyond the photographic image. Mitchell Beazley, 1999.

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Photographing creative landscapes: Simple tools for artistic images and enhanced creativity. Amherst Media, Inc., 2001.

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Image art workshop: Creative ways to embellish and enhance photographic images. CPi Lifestyles, 2009.

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First impressions: Tips to enhance your image. Addicus Books, 1996.

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Rajalingam, Mallikka. Text Segmentation and Recognition for Enhanced Image Spam Detection. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-53047-1.

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Kani, Bijan. Enhanced logical adaptive systems for image processing and pattern recognition. Brunel University, 1993.

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7

R, Beck, ed. Contrast-enhanced MRI of the breast. 2nd ed. Springer, 1996.

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Contrast-enhanced MRI of the breast. Karger, 1990.

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Glossop, N. D. W. Image-enhanced backlighting: a new method of NDE for translucent composites. [s.n.], 1989.

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10

Parente, Diane. Mastering your professional image: Dressing to enhance your credibility. Image Development and Management, 1995.

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Book chapters on the topic "Enhanced images"

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Albouy-Kissi, Adelaide, Stephane Cormier, Bertrand Zavidovique, and Francois Tranquart. "Contrast Enhanced Ultrasound Images Restoration." In Advanced Concepts for Intelligent Vision Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23687-7_36.

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Wang, Zichi, Guorui Feng, and Xinpeng Zhang. "Steganographic Distortion Function for Enhanced Images." In Digital Forensics and Watermarking. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69449-4_3.

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Vojíř, Tomáš, and Jiří Matas. "The Enhanced Flock of Trackers." In Registration and Recognition in Images and Videos. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-44907-9_6.

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Mingo, Luis F., Fernando Arroyo, Carmen Luengo, and Juan Castellanos. "Enhanced Neural Networks and Medical Imaging." In Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48375-6_19.

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Ehlers, Arne, Florian Baumann, Ralf Spindler, Birgit Glasmacher, and Bodo Rosenhahn. "PCA Enhanced Training Data for Adaboost." In Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23672-3_50.

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Yahya, Abid. "An Enhanced Robust and Protected Image Steganographic System." In Steganography Techniques for Digital Images. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78597-4_4.

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Gupta, Renu. "Enhanced Edge Detection Technique for Satellite Images." In Cloud Computing and Security. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48671-0_25.

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Maheswari, D., and V. Radha. "Enhanced Hybrid Compression Models for Compound Images." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24043-0_27.

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Al Ismaeil, Kassem, Djamila Aouada, Bruno Mirbach, and Björn Ottersten. "Depth Super-Resolution by Enhanced Shift and Add." In Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40246-3_13.

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Wang, Tiesheng, Irene Yu-Hua Gu, and Tardi Tjahjadi. "Enhanced Landmine Detection from Low Resolution IR Image Sequences." In Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03767-2_150.

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Conference papers on the topic "Enhanced images"

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Mohammad, Fatimah, and A. Munir. "Image Compression via Dithering for Enhanced Images." In 2007 International Conference on Electrical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/icee.2007.4287322.

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Mahmood, Zahid, and Paul Scheunders. "Enhanced visualization of hyperspectral images." In IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5652813.

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Schwall, Matthew L., Daniel E. Rosenfeld, and Joel C. Wilson. "Enhanced Tire Mark Visualization Using Polarization Imaging." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63953.

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Accident reconstructions often rely on measurements of tire marks left on the roadway surface. However, accurate identification and measurement of these marks can be challenging when the marks are faint, as is often the case with braking marks left by vehicles equipped with anti-lock (ABS) brakes. This paper describes an image processing technique that exploits differences in the polarization of reflected light to create images that significantly enhance tire mark visualization. The technique requires multiple photographs taken from the same perspective, but with a polarizing filter oriented a

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Saji, Nimi Susan, and Ranjitha Rajan. "Identification of source-enhanced composite images." In 2016 International Conference on Emerging Technological Trends (ICETT). IEEE, 2016. http://dx.doi.org/10.1109/icett.2016.7873666.

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Chalmers, Alex. "Transmission-enhanced backscatter x-ray images." In International Symposium on Optical Science and Technology, edited by Ralph B. James. SPIE, 2001. http://dx.doi.org/10.1117/12.450749.

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Lausch, Anthony, Mehran Ebrahimi, and Anne Martel. "Image registration for abdominal dynamic contrast-enhanced magnetic resonance images." In 2011 8th IEEE International Symposium on Biomedical Imaging (ISBI 2011). IEEE, 2011. http://dx.doi.org/10.1109/isbi.2011.5872469.

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Turki, Houssem, Mohamed Ben Halima, and Adel M. Alimi. "Scene text detection images with pyramid image and MSER enhanced." In 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2015. http://dx.doi.org/10.1109/isda.2015.7489243.

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Chatterjee, Chanchal, and Vwani P. Roychowdhury. "Efficient image processing algorithms for enhanced desired gray-scale images." In SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, edited by Andrew G. Tescher. SPIE, 1993. http://dx.doi.org/10.1117/12.158651.

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Amirshahi, Seyed Ali, Altynay Kadyrova, and Marius Pedersen. "How Do Image Quality Metrics Perform on Contrast Enhanced Images?" In 2019 8th European Workshop on Visual Information Processing (EUVIP). IEEE, 2019. http://dx.doi.org/10.1109/euvip47703.2019.8946143.

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N. França, Rodrigo, David A. Ribeiro, Renata L. Rosa, and Demostenes Z. Rodriguez. "Iris image quality on enhanced biometric recognition performance." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.970.

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Nowadays, recognition patterns play an important role in several applications, in which the iris recognition is widely developed in authentication systems today. For such systems models, it is necessary to use as input high quality images, which will reduce possible recognition errors. Thus, this article develops experimental tests to study the image quality on the performance of the iris recognition, using different quality metrics. Thus, experiments are conducted with different iris images and applying the Hamming distance algorithm as reference measurement to accept or denied an user authen

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Reports on the topic "Enhanced images"

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Khalsa, Kimberly A., and Jeffery A. Fessler. Regularized Reconstruction of Dynamic Contrast-Enhanced MR Images for Evaluation of Breast Lesions. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada535361.

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Khalsa, Kimberly A. Regularized Reconstruction of Dynamic Contrast-Enhanced MR Images for Evaluation of Breast Lesions. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada542286.

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Khalsa, Kimberly A. Regularized Reconstruction of Dynamic Contrast-Enhanced MR Images for Evaluation of Breast Lesions. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada514609.

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McIntosh, Robert E. Use of Microwave Polarimetry to Enhance SAR Images of the Ocean Surface. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada273568.

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Choung, George P. A Shape Preserving and Noise Removing Image Enhancer through Regularization. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada387116.

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Wilford, J., and D. Roberts. Enhanced bare earth Landsat imagery for soil and lithological modelling. Geoscience Australia, 2020. http://dx.doi.org/10.11636/134472.

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Cui, Yonggang. Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1477475.

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Cui, Yonggang, and Maikael A. Thomas. Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1436246.

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Cui, Y. Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1413952.

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Cui, Yonggang. Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1524538.

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