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Journal articles on the topic 'Depth of field'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Baylin, Eric. "Depth of Field/Depth of Understanding." Schools 7, no. 1 (2010): 86–100. http://dx.doi.org/10.1086/651297.

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2

Harper, Graeme. "Depth of Field." Creative Industries Journal 11, no. 3 (2018): 223–24. http://dx.doi.org/10.1080/17510694.2018.1534414.

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3

Değirmenci, Koray. "Depth of field." Philosophy of Photography 5, no. 2 (2014): 123–29. http://dx.doi.org/10.1386/pop.5.2.123_7.

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4

Vasudevan, Krishnan. "Depth of Field." Journalism Practice 13, no. 2 (2018): 229–46. http://dx.doi.org/10.1080/17512786.2017.1419826.

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5

Brown, Deeadra. "Depth of field." Dialectical Anthropology 33, no. 2 (2009): 201–2. http://dx.doi.org/10.1007/s10624-009-9115-8.

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6

Soler, Cyril, Kartic Subr, Frédo Durand, Nicolas Holzschuch, and François Sillion. "Fourier depth of field." ACM Transactions on Graphics 28, no. 2 (2009): 1–12. http://dx.doi.org/10.1145/1516522.1516529.

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7

Zhang, Tingting, Louise O’hare, Paul B. Hibbard, Harold T. Nefs, and Ingrid Heynderickx. "Depth of Field Affects Perceived Depth in Stereographs." ACM Transactions on Applied Perception 11, no. 4 (2015): 1–18. http://dx.doi.org/10.1145/2667227.

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8

Landers, Mark N., and David S. Mueller. "Evaluation of Selected Pier-Scour Equations Using Field Data." Transportation Research Record: Journal of the Transportation Research Board 1523, no. 1 (1996): 186–95. http://dx.doi.org/10.1177/0361198196152300123.

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Field measurements of channel scour at bridges are needed to improve the understanding of scour processes and the ability to accurately predict scour depths. An extensive data base of pier-scour measurements has been developed over the last several years in cooperative studies between state highway departments, the Federal Highway Administration, and the U.S. Geological Survey. Selected scour processes and scour design equations are evaluated using 139 measurements of local scour in live-bed and clear-water conditions. Pier-scour measurements were made at 44 bridges around 90 bridge piers in 1

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9

Moon, Won-Leep. "Depth of field and magnification." journal of the moving image technology associon of korea 1, no. 12 (2010): 25–41. http://dx.doi.org/10.34269/mitak.2010.1.12.002.

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10

Geuens, Jean-Pierre. "The Depth of the Field." Quarterly Review of Film and Video 31, no. 6 (2014): 572–85. http://dx.doi.org/10.1080/10509208.2012.686812.

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11

Kuthirummal, S., H. Nagahara, Changyin Zhou, and S. K. Nayar. "Flexible Depth of Field Photography." IEEE Transactions on Pattern Analysis and Machine Intelligence 33, no. 1 (2011): 58–71. http://dx.doi.org/10.1109/tpami.2010.66.

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12

Birkerts, Sven. "Reading and Depth of Field." Philosophy and Literature 20, no. 1 (1996): 122–29. http://dx.doi.org/10.1353/phl.1996.0004.

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13

Langan, Robert. "The Depth of the Field." Contemporary Psychoanalysis 29, no. 4 (1993): 628–44. http://dx.doi.org/10.1080/00107530.1993.10746829.

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14

Kim, Jaewon, Roarke Horstmeyer, Ig-Jae Kim, and Ramesh Raskar. "Highlighted depth-of-field photography." ACM Transactions on Graphics 30, no. 3 (2011): 1–9. http://dx.doi.org/10.1145/1966394.1966403.

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15

Poncet, Aurelie M., John P. Fulton, Timothy P. McDonald, Thorsten Knappenberger, Joey N. Shaw, and Rees W. Bridges. "Effect of Heterogeneous Field Conditions on Corn Seeding Depth Accuracy and Uniformity." Applied Engineering in Agriculture 34, no. 5 (2018): 819–30. http://dx.doi.org/10.13031/aea.12238.

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Abstract. Optimization of planter performance such as uniform seeding depth is required to maximize crop yield potential. Typically, seeding depth is manually adjusted prior to planting by selecting a row-unit depth and a row-unit downforce to ensure proper seed-soil contact. Once set, row-unit depth and downforce are usually not adjusted again for a field although soil conditions may vary. Optimization of planter performance requires automated adjustments of planter settings to varying soil conditions, but development of precision technologies with such capabilities requires a better understa

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16

Pidhorskyi, Stanislav, Timur Bagautdinov, Shugao Ma, et al. "Depth of Field Aware Differentiable Rendering." ACM Transactions on Graphics 41, no. 6 (2022): 1–18. http://dx.doi.org/10.1145/3550454.3555521.

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Cameras with a finite aperture diameter exhibit defocus for scene elements that are not at the focus distance, and have only a limited depth of field within which objects appear acceptably sharp. In this work we address the problem of applying inverse rendering techniques to input data that exhibits such defocus blurring. We present differentiable depth-of-field rendering techniques that are applicable to both rasterization-based methods using mesh representations, as well as ray-marching-based methods using either explicit [Yu et al. 2021] or implicit volumetric radiance fields [Mildenhall et

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17

Mauderer, M., S. I. Conte, M. A. Nacenta, and D. Vishwanath. "Using Gaze-Contingent Depth of Field to Facilitate Depth Perception." i-Perception 5, no. 5 (2014): 473. http://dx.doi.org/10.1068/ii42.

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18

Li, B. "Simulation analysis of temperature field of permafrost roadbed." E3S Web of Conferences 136 (2019): 04077. http://dx.doi.org/10.1051/e3sconf/201913604077.

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The finite element analysis model of roadbed temperature field in permafrost region is established with finite element software platform. By using this model, the temperature field of roadbed is compared and analysed, and the freezing-thawing depth and variation rule of roadbed are studied. The results showed that the actual freezing depth was 1.8m. With the increase of the climate warming temperature, the temperature field in the roadbed changes slowly, and the temperature at different depths increases. Due to the influence of climate warming, the roadbed was in a complete positive temperatur

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19

Johnston, Adrian M., and F. Craig Stevenson. "Field pea response to seeding depth and P fertilization." Canadian Journal of Plant Science 81, no. 3 (2001): 573–75. http://dx.doi.org/10.4141/p00-166.

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A study was conducted at Melfort, SK, in 1998 and 1999 to determine whether seeding depth and P fertilization affect field pea (Pisum sativum L.) seedling emergence and grain yield. Treatments included a factorial combination of three seeding depths (38 mm, 76 mm, and 114 mm) with and without 25 kg P2O5 ha–1 as monoammonium phosphate. While seedling density was not affected by seeding depth at 3 wk after planting, the deepest seeding depth produced significantly fewer seedlings than the two shallower depths at 5 wk post-seeding. A year-by-seeding-depth interaction was recorded for grain yield,

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20

Hu, Jing, Sunzheng Li, Yibing Shen, JinLei Zhang, and Zhenrong Zheng. "Extended depth of field reconstruction with complex field estimation." Optics & Laser Technology 152 (August 2022): 108118. http://dx.doi.org/10.1016/j.optlastec.2022.108118.

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21

Abdelaal, Ahmed M., Ehab M. Attalla, and Wael M. Elshemey. "Estimation of Out-of-Field Dose Variation using Markus Ionization Chamber Detector." SciMedicine Journal 2, no. 1 (2020): 8–15. http://dx.doi.org/10.28991/scimedj-2020-0201-2.

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Objective: The aim of This work to provide evaluation for the out-of-field dose with different plan parameters as field size and depth using Markus ionization chamber detector in the measurement that are frequently used in electron and superficial dosimetery, in radiotherapy. Methods: This is carried out through the application of these detector in estimation of the out-of-field dose with important dosimetric parameters such as field size (from 5×5 to 30×30 cm2) and depth (from 1.5 to 30 cm) at energy 6 MV and collimator angle 0° at SSD 100 cm. Results: Results show that, the Markus detector r

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22

Higginbotham, J. H., Y. Shin, and D. V. Sukup. "Directional depth migration." GEOPHYSICS 50, no. 11 (1985): 1784–89. http://dx.doi.org/10.1190/1.1441867.

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Complicated geologic structures such as folds, overthrusts, and salt domes can produce reflectors with dips as great as 90 degrees. Because oil and gas accumulations are often associated with these steeply dipping interfaces, accurate processing of reflection seismic information from such areas becomes an important though challenging task. The proper imaging of steeply dipping reflectors requires accurate knowledge of the velocity field through which the wavefronts propagate. Thus, velocity analysis becomes extremely important. In addition to this problem, most migration algorithms have seriou

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23

O'Hare, Louise, Tingting Zhang, Harold T. Nefs, and Paul B. Hibbard. "Visual Discomfort and Depth-of-Field." i-Perception 4, no. 3 (2013): 156–69. http://dx.doi.org/10.1068/i0566.

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24

Grobbe, Niels, Joost van der Neut, Evert Slob, Kees Wapenaar, Carlos Almagro Vidal, and Guy Drijkoningen. "Unified multi-depth-level field decomposition." Geophysical Prospecting 64, no. 2 (2015): 361–91. http://dx.doi.org/10.1111/1365-2478.12290.

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25

Ledesma-Carrillo, Luis, Rafael Guzmán-Cabrera, Cristina M. Gómez-Sarabia, Miguel Torres-Cisneros, and Jorge Ojeda-Castañeda. "Tunable field depth: hyperbolic optical masks." Applied Optics 56, no. 1 (2016): A104. http://dx.doi.org/10.1364/ao.56.00a104.

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26

Maurer, Christian, Saranjam Khan, Stephanie Fassl, Stefan Bernet, and Monika Ritsch-Marte. "Depth of field multiplexing in microscopy." Optics Express 18, no. 3 (2010): 3023. http://dx.doi.org/10.1364/oe.18.003023.

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27

Higbie, Jack. "Depth of field in hologram images." Physics Teacher 35, no. 7 (1997): 418–19. http://dx.doi.org/10.1119/1.2344743.

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28

Gori, Paola, Gabriella Cincotti, and Massimo Pappalardo. "Beams with large depth of field." Journal of the Acoustical Society of America 107, no. 5 (2000): 2782. http://dx.doi.org/10.1121/1.428945.

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29

Meck, E., and V. Sirivivatnanon. "Field indicator of chloride penetration depth." Cement and Concrete Research 33, no. 8 (2003): 1113–17. http://dx.doi.org/10.1016/s0008-8846(03)00012-7.

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30

Sheppard, C. J. R. "Depth of field in optical microscopy." Journal of Microscopy 149, no. 1 (1988): 73–75. http://dx.doi.org/10.1111/j.1365-2818.1988.tb04563.x.

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31

Zhang, Lei, Jianpeng Fan, and Jungang Yang. "Blind-Depth Light Field Super-Resolution." Journal of Physics: Conference Series 1575 (June 2020): 012051. http://dx.doi.org/10.1088/1742-6596/1575/1/012051.

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32

Gómez-Sarabia, Cristina M., Luis Ledesma-Carrillo, and Jorge Ojeda-Castañeda. "Reducing field depth: annular Hadamard masks." Applied Optics 59, no. 22 (2020): 6632. http://dx.doi.org/10.1364/ao.397862.

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33

Kim, Hyun Myung, Min Seok Kim, Sehui Chang, Jiseong Jeong, Hae-Gon Jeon, and Young Min Song. "Vari-Focal Light Field Camera for Extended Depth of Field." Micromachines 12, no. 12 (2021): 1453. http://dx.doi.org/10.3390/mi12121453.

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The light field camera provides a robust way to capture both spatial and angular information within a single shot. One of its important applications is in 3D depth sensing, which can extract depth information from the acquired scene. However, conventional light field cameras suffer from shallow depth of field (DoF). Here, a vari-focal light field camera (VF-LFC) with an extended DoF is newly proposed for mid-range 3D depth sensing applications. As a main lens of the system, a vari-focal lens with four different focal lengths is adopted to extend the DoF up to ~15 m. The focal length of the mic

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34

Lee, Fong-Zuo, Jihn-Sung Lai, Yuan-Bin Lin, Kuo-Chun Chang, Xiaoqin Liu, and Cheng-Chia Huang. "Prediction of Bridge Pier Scour Depth and Field Scour Depth Monitoring." E3S Web of Conferences 40 (2018): 03007. http://dx.doi.org/10.1051/e3sconf/20184003007.

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In practice, it is a major challenge in real-time simulation and prediction of bridge pier scour depth, especially using 3-D numerical model. The simulation time spend too much to use 3-D numerical model simulation and inefficiently to predict bridge pier scour depth in real-time. With heavy rainfall during flood season in Taiwan, abundant sediment with flash flood from upstream watershed is transported to downstream river reaches and transportation time is limited within one day. The flood flow tends to damage bridge structures and affect channel stabilization in fluvial rivers. In addition,

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35

Navarro, Hector, Genaro Saavedra, Manuel Martinez-Corral, Marten Sjostrom, and Roger Olsson. "Depth-of-Field Enhancement in Integral Imaging by Selective Depth-Deconvolution." Journal of Display Technology 10, no. 3 (2014): 182–88. http://dx.doi.org/10.1109/jdt.2013.2291110.

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36

Choi, Sungwon, and Sung-wook Min. "Depth estimation method using depth-of-field imaging with a retroreflector." Optics Express 26, no. 5 (2018): 5655. http://dx.doi.org/10.1364/oe.26.005655.

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37

Jin, Xin, Zhouping Wang, Xiaoyu Wang, and Qionghai Dai. "Depth of field extended scattering imaging by light field estimation." Optics Letters 43, no. 20 (2018): 4871. http://dx.doi.org/10.1364/ol.43.004871.

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38

Ji, Jiaxin, Pengfei Xu, Jiying Chen, Jing Li, and Yonggang Meng. "High Depth-of-Field Nanostructures by Rotational Near-Field Photolithography." Plasmonics 15, no. 1 (2019): 209–15. http://dx.doi.org/10.1007/s11468-019-01026-4.

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39

Mottram, Ruth H., and Douglas I. Benn. "Testing crevasse-depth models: a field study at Breiðamerkurjökull, Iceland." Journal of Glaciology 55, no. 192 (2009): 746–52. http://dx.doi.org/10.3189/002214309789470905.

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AbstractInterest in crevasses and associated ice-fracture processes has recently increased due to recognition of the importance of calving glaciers to the mass balance of the cryosphere, as well as the importance of fractures in glacier hydrology. Recently developed calving criteria make use of models which predict crevasse depth from surface strain rates, but these models have rarely been tested against observations. In this study, we present data on crevasse depth and surface strain rates, and compare the measured values with results of two crevasse-depth models: a simple function proposed b

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40

Cushman, Kent E., Muhammad Maqbool, and Patrick D. Gerard. "Mulch Type, Mulch Depth, and Rhizome Planting Depth for Field-grown American Mayapple." HortScience 40, no. 3 (2005): 635–39. http://dx.doi.org/10.21273/hortsci.40.3.635.

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American mayapple (Podophyllum peltatum L.) is a rhizomatous herbaceous perennial found in wooded areas of eastern North America and is a source of the pharmaceutical compound podophyllotoxin. To explore the possible domestication of this species, this research examined strategies for establishing mayapple in field plantings using organic mulches. Mayapple rhizome segments were harvested from the wild and transplanted to raised beds in northern Mississippi in Fall 2001. Two types of mulch (pine bark or wheat straw), two depths of mulch (7.5 or 15 cm), and two planting depths (0 or 5 cm) of rhi

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41

Esehaghbeygi, Ali, Milad Abedi, Jalil Razavi, and Abbass Hemmat. "Field evaluation of a vibrating dual bent-share cultivator." Research in Agricultural Engineering 66, No. 4 (2020): 123–30. http://dx.doi.org/10.17221/49/2020-rae.

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In this research, the suitability of a vibrating dual bent-share cultivator was studied. Therefore, an eccentric pin-slider mechanism was designed to vibrate the two shanks laterally, using a tractor power take-off. The present study investigates the field performance of the vibrating dual bent-share cultivator with three different vibration frequencies (0, 0.88, and 2 Hz) in a clay loam soil at two working depths (100 and 200 mm) and having a water content of a 0.7 or 0.9 plastic limit. The lowest values of the draught, specific draught, and MWD were recorded at a vibration frequency of 2 Hz

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42

Xu, Lei, Terry Olson, Byron Lengsfield, Masato Shiimoto, Mikito Sugiyama, and Adam Torabi. "The Importance of Depth-Varying Fields for MAMR Switching-Field Reduction." IEEE Transactions on Magnetics 51, no. 11 (2015): 1–3. http://dx.doi.org/10.1109/tmag.2015.2437074.

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43

Fedi, Maurizio, and Mark Pilkington. "Understanding imaging methods for potential field data." GEOPHYSICS 77, no. 1 (2012): G13—G24. http://dx.doi.org/10.1190/geo2011-0078.1.

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Several noniterative, imaging methods for potential field data have been proposed that provide an estimate of the 3D magnetization/density distribution within the subsurface or that produce images of quantities related or proportional to such distributions. They have been derived in various ways, using generalized linear inversion, Wiener filtering, wavelet and depth from extreme points (DEXP) transformations, crosscorrelation, and migration. We demonstrated that the resulting images from each of these approaches are equivalent to an upward continuation of the data, weighted by a (possibly) de

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44

Lee, Jeseon, and Sungkil Lee. "Real-Time Depth-of-Field Rendering Using Depth Range Shift and Compression." Journal of KIISE 46, no. 11 (2019): 1106–12. http://dx.doi.org/10.5626/jok.2019.46.11.1106.

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45

Zhao, Mandan, Gaochang Wu, Yebin Liu, and Xiangyang Hao. "How depth estimation in light fields can benefit from super-resolution?" International Journal of Advanced Robotic Systems 15, no. 1 (2018): 172988141774844. http://dx.doi.org/10.1177/1729881417748446.

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With the development of consumer light field cameras, the light field imaging has become an extensively used method for capturing the three-dimensional appearance of a scene. The depth estimation often requires a dense sampled light field in the angular domain or a high resolution in the spatial domain. However, there is an inherent trade-off between the angular and spatial resolutions of the light field. Recently, some studies for super-resolving the trade-off light field have been introduced. Rather than the conventional approaches that optimize the depth maps, these approaches focus on maxi

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46

Kumar, Hemendra, Puneet Srivastava, Brenda V. Ortiz, et al. "Field-Scale Spatial and Temporal Soil Water Variability in Irrigated Croplands." Transactions of the ASABE 64, no. 4 (2021): 1277–94. http://dx.doi.org/10.13031/trans.14335.

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HighlightsThe greatest heterogeneity in soil water was observed at 30-60 cm depth in a corn field and 0-15 cm in a cotton field.Spatiotemporal soil water variability did not increase with increasing soil water in all soil layers in both croplands during the growing season.Water excess and water stress locations were identified in both fields. A single, temporally stable location was identified in each field, which can be used for precise uniform irrigation.Knowledge of variability and stability in soil water can be useful in determining the number and location of sensors to install in crop fie

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47

Palmieri, Luca, Gabriele Scrofani, Nicolò Incardona, Genaro Saavedra, Manuel Martínez-Corral, and Reinhard Koch. "Robust Depth Estimation for Light Field Microscopy." Sensors 19, no. 3 (2019): 500. http://dx.doi.org/10.3390/s19030500.

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Light field technologies have seen a rise in recent years and microscopy is a field where such technology has had a deep impact. The possibility to provide spatial and angular information at the same time and in a single shot brings several advantages and allows for new applications. A common goal in these applications is the calculation of a depth map to reconstruct the three-dimensional geometry of the scene. Many approaches are applicable, but most of them cannot achieve high accuracy because of the nature of such images: biological samples are usually poor in features and do not exhibit sh

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48

Xiaomin, LIU, MA Zhibang, WANG Qiancheng, et al. "Compression light field reconstruction and depth estimation." Journal of Applied Optics 40, no. 2 (2019): 1–8. http://dx.doi.org/10.5768/jao201940.0201001.

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49

Mishiba, Kazu. "Fast Depth Estimation for Light Field Cameras." IEEE Transactions on Image Processing 29 (2020): 4232–42. http://dx.doi.org/10.1109/tip.2020.2970814.

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50

Cowley, R. G. "Depth conversion problems of the SKUA field." Exploration Geophysics 20, no. 2 (1989): 297. http://dx.doi.org/10.1071/eg989297.

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Before oil volumes and economics can be calculated for an oil field, the seismic time map must be converted to a depth map. The Skua Field, located in Permit AC/P2 in the Timor Sea, has proved particularly difficult to depth convert. Velocity anomalies and inconsistencies in the seismic times, termed 'lags', have created distortions in the seismic time map which require compensation. Beneath a velocity anomaly, both seismic undershoot and increased velocity, which are difficult to determine, must be compensated for during depth conversion. The current depth map was produced by smoothing throug

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