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Relevant bibliographies by topics / Image quality estimation

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Academic literature on the topic 'Image quality estimation'

Author: Grafiati

Published: 10 March 2023

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Journal articles on the topic "Image quality estimation"

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Chin, Sin Chee, Chee-Onn Chow, Jeevan Kanesan, and Joon Huang Chuah. "A Study on Distortion Estimation Based on Image Gradients." Sensors 22, no. 2 (2022): 639. http://dx.doi.org/10.3390/s22020639.

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Image noise is a variation of uneven pixel values that occurs randomly. A good estimation of image noise parameters is crucial in image noise modeling, image denoising, and image quality assessment. To the best of our knowledge, there is no single estimator that can predict all noise parameters for multiple noise types. The first contribution of our research was to design a noise data feature extractor that can effectively extract noise information from the image pair. The second contribution of our work leveraged other noise parameter estimation algorithms that can only predict one type of no

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Temel, Dogancan, Mohit Prabhushankar, and Ghassan AlRegib. "UNIQUE: Unsupervised Image Quality Estimation." IEEE Signal Processing Letters 23, no. 10 (2016): 1414–18. http://dx.doi.org/10.1109/lsp.2016.2601119.

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Wang, Qiu Yun. "Depth Estimation Based Underwater Image Enhancement." Advanced Materials Research 926-930 (May 2014): 1704–7. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.1704.

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According to the image formation model and the nature of underwater images, we find that the effect of the haze and the color distortion seriously pollute the underwater image data, lowing the quality of the underwater images in the visibility and the quality of the data. Hence, aiming to reduce the noise and the haze effect existing in the underwater image and compensate the color distortion, the dark channel prior model is used to enhance the underwater image. We compare the dark channel prior model based image enhancement method to the contrast stretching based method for image enhancement.

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Li, Chao, Mingyang Li, Jie Liu, Yingchang Li, and Qianshi Dai. "Comparative Analysis of Seasonal Landsat 8 Images for Forest Aboveground Biomass Estimation in a Subtropical Forest." Forests 11, no. 1 (2019): 45. http://dx.doi.org/10.3390/f11010045.

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To effectively further research the regional carbon sink, it is important to estimate forest aboveground biomass (AGB). Based on optical images, the AGB can be estimated and mapped on a regional scale. The Landsat 8 Operational Land Imager (OLI) has, therefore, been widely used for regional scale AGB estimation; however, most studies have been based solely on peak season images without performance comparison of other seasons; this may ultimately affect the accuracy of AGB estimation. To explore the effects of utilizing various seasonal images for AGB estimation, we analyzed seasonal images col

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Xu, Ningshan, Dongao Ma, Guoqiang Ren, and Yongmei Huang. "BM-IQE: An Image Quality Evaluator with Block-Matching for Both Real-Life Scenes and Remote Sensing Scenes." Sensors 20, no. 12 (2020): 3472. http://dx.doi.org/10.3390/s20123472.

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Like natural images, remote sensing scene images; of which the quality represents the imaging performance of the remote sensor, also suffer from the degradation caused by imaging system. However, current methods measuring the imaging performance in engineering applications require for particular image patterns and lack generality. Therefore, a more universal approach is demanded to assess the imaging performance of remote sensor without constraints of land cover. Due to the fact that existing general-purpose blind image quality assessment (BIQA) methods cannot obtain satisfying results on remo

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Huang, Penghe, Dongyan Li, and Huimin Zhao. "An Improved Robust Fractal Image Compression Based on M-Estimator." Applied Sciences 12, no. 15 (2022): 7533. http://dx.doi.org/10.3390/app12157533.

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In this paper, a robust fractal image compression method based on M-estimator is presented. The proposed method applies the M-estimator to the parameter estimation in the fractal encoding procedure using Huber and Tukey’s robust statistics. The M-estimation reduces the influence of the outliers and makes the fractal encoding algorithm robust to the noisy image. Meanwhile, the quadtree partitioning approach has been used in the proposed methods to improve the efficiency of the encoding algorithm, and some unnecessary computations are eliminated in the parameter estimation procedures. The experi

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Anikeeva, I., and A. Chibunichev. "RANDOM NOISE ASSESSMENT IN AERIAL AND SATELLITE IMAGES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 771–75. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-771-2021.

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Abstract. Random noise in aerial and satellite images is one of the factors, decreasing their quality. The noise level assessment in images is paid not enough attention. The method of numerical estimation of random image noise is considered. The object of the study is the image noise estimating method, based on harmonic analysis. The capability of using this method for aerial and satellite image quality assessment is considered. The results of the algorithm testing on model data and on real satellite images with different terrain surfaces are carried out. The accuracy estimating results for ca

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Kim, Sangmin, Daekwan Kim, Kilwoo Chung, and JoonSeo Yim. "Estimation of any fields of lens PSFs for image simulation." Electronic Imaging 2021, no. 7 (2021): 72–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.7.iss-072.

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In a mobile smartphone camera, image quality is more degraded towards the edges of an image sensor due to high CRA (Chief Ray Angle). It is critical to estimate the cause of this effect since image quality is degraded at image periphery from attenuating illuminance and broadening PSF (point spread function). In order to predict image quality from the center to the edge of the camera output, we propose a method to estimate lens PSFs at any particular image field. The method adopts Zernike polynomials to consider lens aberrations while having an arbitrary spatial sampling. Also, it employs estim

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Du, Juan. "AIVMAF: Automatic Image Quality Estimation Based on Improved VMAF and YOLOv4." Journal of Physics: Conference Series 2289, no. 1 (2022): 012020. http://dx.doi.org/10.1088/1742-6596/2289/1/012020.

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Abstract The current most widely used way of image quality estimation relies heavily on the subjective assessment, while majority of past objective estimation methods are not satisfactory on accuracy. To solve them and realize unsupervised image quality estimation with high precision, this paper creates a linear way with “Proportional Partition” controlled by horizontal and vertical rates of extracted pixel to get best representations of the image with patching, balance the uneven distribution of image quality in each source image, and offer dynamic compatibility to images with high resolution

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Salokhiddinov, Sherzod, and Seungkyu Lee. "Iterative Refinement of Uniformly Focused Image Set for Accurate Depth from Focus." Applied Sciences 10, no. 23 (2020): 8522. http://dx.doi.org/10.3390/app10238522.

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Estimating the 3D shape of a scene from differently focused set of images has been a practical approach for 3D reconstruction with color cameras. However, reconstructed depth with existing depth from focus (DFF) methods still suffer from poor quality with textureless and object boundary regions. In this paper, we propose an improved depth estimation based on depth from focus iteratively refining 3D shape from uniformly focused image set (UFIS). We investigated the appearance changes in spatial and frequency domains in iterative manner. In order to achieve sub-frame accuracy in depth estimation

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Dissertations / Theses on the topic "Image quality estimation"

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Akinbola, Akintunde A. "Estimation of image quality factors for face recognition." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4308.

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Thesis (M.S.)--West Virginia University, 2005.<br>Title from document title page. Document formatted into pages; contains vi, 56 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 52-56).

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Istenič, Klemen. "Underwater image-based 3D reconstruction with quality estimation." Doctoral thesis, Universitat de Girona, 2021. http://hdl.handle.net/10803/672199.

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This thesis addresses the development of resources for accurate scaling and uncertainty estimation of image-based 3D models for scientific purposes based on data acquired with monocular or unsynchronized camera systems in difficult-to-access GPS-denied (underwater) environments. The developed 3D reconstruction framework allows the creation of textured 3D models based on optical and navigation data and is independent of a specific platform, camera or mission. The dissertation presents two new methods for automatically scaling of SfM-based 3D models using laser scalers. Both were used to perfor

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Cui, Lei. "Topics in image recovery and image quality assessment /Cui Lei." HKBU Institutional Repository, 2016. https://repository.hkbu.edu.hk/etd_oa/368.

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Image recovery, especially image denoising and deblurring is widely studied during the last decades. Variational models can well preserve edges of images while restoring images from noise and blur. Some variational models are non-convex. For the moment, the methods for non-convex optimization are limited. This thesis finds new non-convex optimizing method called difference of convex algorithm (DCA) for solving different variational models for various kinds of noise removal problems. For imaging system, noise appeared in images can show different kinds of distribution due to the different imagi

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Thomas, Graham A. "Motion estimation and its application in broadcast television." Thesis, University of Essex, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.258717.

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Tseng, Hsin-Wu, Jiahua Fan, and Matthew A. Kupinski. "Assessing computed tomography image quality for combined detection and estimation tasks." SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 2017. http://hdl.handle.net/10150/626451.

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Maintaining or even improving image quality while lowering patient dose is always the desire in clinical computed tomography (CT) imaging. Iterative reconstruction (IR) algorithms have been designed to allow for a reduced dose while maintaining or even improving an image. However, we have previously shown that the dose-saving capabilities allowed with IR are different for different clinical tasks. The channelized scanning linear observer (CSLO) was applied to study clinical tasks that combine detection and estimation when assessing CT image data. The purpose of this work is to illustrate the i

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Ghosh, Roy Gourab. "A Simple Second Derivative Based Blur Estimation Technique." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366890068.

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Zhang, Changjun. "Seismic absorption estimation and compensation." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2820.

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As seismic waves travel through the earth, the visco-elasticity of the earth's medium will cause energy dissipation and waveform distortion. This phenomenon is referred to as seismic absorption or attenuation. The absorptive property of a medium can be described by a quality factor Q, which determines the energy decay and a velocity dispersion relationship. Four new ideas have been developed in this thesis to deal with the estimation and application of seismic absorption. By assuming that the amplitude spectrum of a seismic wavelet may be modeled by that of a Ricker wavelet, an analytical r

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Nezhadarya, Ehsan. "Image derivative estimation and its applications to edge detection, quality monitoring and copyright protection." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44504.

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Multi-order image derivatives are used in many image processing and computer vision applications, such as edge detection, feature extraction, image enhancement, segmentation, matching, watermarking and quality assessment. In some applications, the image derivatives are modified and then inverse-transformed to the image domain. For example, one approach for image denoising is to keep the significant image derivatives and shrink the non-significant derivatives. The denoised image is then reconstructed from the modified derivatives. The main challenge here is how to inverse-transform the derivati

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Fuin, N. "Estimation of the image quality in emission tomography : application to optimization of SPECT system design." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1417803/.

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In Emission Tomography the design of the Imaging System has a great influence on the quality of the output image. Optimisation of the system design is a difficult problem due to the computational complexity and to the challenges in its mathematical formulation. In order to compare different system designs, an efficient and effective method to calculate the Image Quality is needed. In this thesis the statistical and deterministic methods for the calculation of the uncertainty in the reconstruction are presented. In the deterministic case, the Fisher Information Matrix (FIM) formalism can be emp

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Al, Chami Zahi. "Estimation de la qualité des données multimedia en temps réel." Thesis, Pau, 2021. http://www.theses.fr/2021PAUU3066.

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Au cours de la dernière décennie, les fournisseurs de données ont généré et diffusé une grande quantité de données, notamment des images, des vidéos, de l'audio, etc. Dans cette thèse, nous nous concentrerons sur le traitement des images puisqu'elles sont les plus communément partagées entre les utilisateurs sur l'inter-réseau mondial. En particulier, le traitement des images contenant des visages a reçu une grande attention en raison de ses nombreuses applications, telles que les applications de divertissement et de médias sociaux. Cependant, plusieurs défis pourraient survenir au cours de la

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Books on the topic "Image quality estimation"

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Jensen, Jørgen Arendt. Medical ultrasound imaging: An estimation based approach. Electronics Laboratory, Technical University of Denmark, 1988.

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Kondo, Kazuhiro. Subjective Quality Measurement of Speech: Its Evaluation, Estimation and Applications. Springer Berlin Heidelberg, 2012.

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Kondo, Kazuhiro. Subjective Quality Measurement of Speech: Its Evaluation, Estimation and Applications. Springer, 2014.

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Book chapters on the topic "Image quality estimation"

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Li, Qin, and Bin Xie. "Image-Based Air Quality Estimation." In Pattern Recognition and Computer Vision. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31726-3_14.

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Aichinger, Horst, Joachim Dierker, Sigrid Joite-Barfuß, and Manfred Säbel. "Patient Dose Estimation." In Radiation Exposure and Image Quality in X-Ray Diagnostic Radiology. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11241-6_18.

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Aichinger, Horst, Joachim Dierker, Sigrid Joite-Barfuß, and Manfred Säbel. "Patient Dose Estimation." In Radiation Exposure and Image Quality in X-Ray Diagnostic Radiology. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-09654-3_17.

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Liu, Haoting, Jin Yang, Wei Wang, Zhexi He, and Wenpeng Yu. "Illumination Effect Estimation Based on Image Quality Assessment." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48224-7_35.

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Martínez-Usó, Adolfo, Filiberto Pla, and Pedro García-Sevilla. "Multispectral Image Segmentation by Energy Minimization for Fruit Quality Estimation." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492542_84.

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Zhu, En, Jianping Yin, Chunfeng Hu, and Guomin Zhang. "Quality Estimation of Fingerprint Image Based on Neural Network." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11539117_10.

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Mangulkar, Madhuri N., Suddhasheel Ghosh, and Sanjay S. Jamkar. "Estimation of Aggregate Characteristics Using Digital Image Processing." In ICRRM 2019 – System Reliability, Quality Control, Safety, Maintenance and Management. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8507-0_2.

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Hernandez-Ortega, Javier, Shigenori Nagae, Julian Fierrez, and Aythami Morales. "Quality-Based Pulse Estimation from NIR Face Video with Application to Driver Monitoring." In Pattern Recognition and Image Analysis. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31321-0_10.

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Jaramillo, Miguel A., J. álvaro Fernández, José M. Montanero, and Fernando Zayas. "Image Quality Enhancement for Liquid Bridge Parameter Estimation with DTCNN." In Bio-Inspired Applications of Connectionism. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45723-2_29.

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Wang, Ren-Jie, Yan-Ting Jiang, Jiunn-Tsair Fang, and Pao-Chi Chang. "Quality Estimation for H.264/SVC Inter-layer Residual Prediction in Spatial Scalability." In Advances in Image and Video Technology. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25346-1_23.

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Conference papers on the topic "Image quality estimation"

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Efimov, Aleksey I., Dmitry I. Ustukov, and Yevgeniy R. Muratov. "Image Superimposition Quality Estimation Algorithms." In 2020 9th Mediterranean Conference on Embedded Computing (MECO). IEEE, 2020. http://dx.doi.org/10.1109/meco49872.2020.9134163.

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Zhao, Yulan, Chunfeng Jiang, Xiufeng Fang, and Bin Huang. "Research of Fingerprint Image Quality Estimation." In 2009 International Conference on Dependable, Autonomic and Secure Computing (DASC). IEEE, 2009. http://dx.doi.org/10.1109/dasc.2009.112.

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Burns, Peter D. "Estimation error in image quality measurements." In IS&T/SPIE Electronic Imaging, edited by Susan P. Farnand and Frans Gaykema. SPIE, 2011. http://dx.doi.org/10.1117/12.872626.

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Loginov, Aleksandr A., Evgeniy R. Muratov, and Mikhail B. Nikiforov. "Image Quality Estimation Using Integral Indicator." In the International Conference. ACM Press, 2017. http://dx.doi.org/10.1145/3093241.3093250.

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de Angelis, A., A. Moschitta, F. Russo, and P. Carbone. "Image Quality Assessment: an Overview and some Metrological Considerations." In 2007 IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement. IEEE, 2007. http://dx.doi.org/10.1109/amuem.2007.4362569.

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SanMiguel, Juan C., and Andrea Cavallaro. "Efficient estimation of target detection quality." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296414.

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Yoshida, T., and T. Miyata. "Adaptive frame interval control and its quality estimation." In rnational Conference on Image Processing. IEEE, 2005. http://dx.doi.org/10.1109/icip.2005.1530306.

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Guan, Jingwei, and Wai-Kuen Cham. "Quality estimation based multi-focus image fusion." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7952504.

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Shumilov, Yurij P., Peter A. Bakut, Irina A. Grishina, and Victor V. Sychev. "Segmented primary mirror telescope image quality estimation." In Astronomical Telescopes and Instrumentation, edited by Philippe Dierickx. SPIE, 2000. http://dx.doi.org/10.1117/12.391515.

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Demirtas, A. Murat, Amy R. Reibman, and Hamid Jafarkhani. "Image quality estimation for different spatial resolutions." In 2013 20th IEEE International Conference on Image Processing (ICIP). IEEE, 2013. http://dx.doi.org/10.1109/icip.2013.6738078.

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Reports on the topic "Image quality estimation"

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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti

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Saltus, Christina, Molly Reif, and Richard Johansen. waterquality for ArcGIS Pro Toolbox. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42240.

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Monitoring water quality of small inland lakes and reservoirs is a critical component of USACE water quality management plans. However, limited resources for traditional field-based monitoring of numerous lakes and reservoirs that cover vast geographic areas often leads to reactional responses to harmful algal bloom (HAB) outbreaks. Satellite remote sensing methodologies using HAB indicators is a good low-cost option to traditional methods and has been proven to maximize and complement current field-based approaches while providing a synoptic view of water quality (Beck et al. 2016; Beck et al

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Saltus, Christina, Molly Reif, and Richard Johansen. waterquality for ArcGIS Pro Toolbox : user's guide. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45362.

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Monitoring water quality of small inland lakes and reservoirs is a critical component of the US Army Corps of Engineers (USACE) water quality management plans. However, limited resources for traditional field-based monitoring of numerous lakes and reservoirs covering vast geographic areas often leads to reactional responses to harmful algal bloom (HAB) outbreaks. Satellite remote sensing methodologies using HAB indicators is a good low-cost option to traditional methods and has been proven to maximize and complement current field-based approaches while providing a synoptic view of water qualit

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Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water

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