標(biāo)題: Titlebook: Depth From Defocus: A Real Aperture Imaging Approach; Subhasis Chaudhuri,A. N. Rajagopalan Book 1999 Springer Science+Business Media New Y [打印本頁] 作者: Systole 時間: 2025-3-21 17:17
書目名稱Depth From Defocus: A Real Aperture Imaging Approach影響因子(影響力)
書目名稱Depth From Defocus: A Real Aperture Imaging Approach影響因子(影響力)學(xué)科排名
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書目名稱Depth From Defocus: A Real Aperture Imaging Approach網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Depth From Defocus: A Real Aperture Imaging Approach被引頻次
書目名稱Depth From Defocus: A Real Aperture Imaging Approach被引頻次學(xué)科排名
書目名稱Depth From Defocus: A Real Aperture Imaging Approach年度引用
書目名稱Depth From Defocus: A Real Aperture Imaging Approach年度引用學(xué)科排名
書目名稱Depth From Defocus: A Real Aperture Imaging Approach讀者反饋
書目名稱Depth From Defocus: A Real Aperture Imaging Approach讀者反饋學(xué)科排名
作者: Infusion 時間: 2025-3-21 20:19
https://doi.org/10.1007/978-94-009-6475-4obtaining a filtered output by an inverse operation, assuming that the inverse exists. This is an intuitive generalization of time-invariant filtering. The nature of the resultant time-variant filter depends on the type of the TFR chosen.作者: 頭盔 時間: 2025-3-22 01:10 作者: tariff 時間: 2025-3-22 06:10
d autonomous vehicle guidance. These tasks are performed in a 3-D world and it is imperative to gather reliable information on the 3-D structure of the scene. This book is about passive techniques for depth recovery, where the scene is illuminated only by natural light as opposed to active methods w作者: indifferent 時間: 2025-3-22 10:56
https://doi.org/10.1007/978-94-009-6475-4ve blur between the defocused images is measured to obtain an estimate of the depth of the scene. Neither of the images needs to be focused. In its generality, recovering the depth from defocused images is equivalent to the space-variant blur identification problem. Some of the important advantages of the DFD method are as follows.作者: Malfunction 時間: 2025-3-22 15:46
Conclusions,ve blur between the defocused images is measured to obtain an estimate of the depth of the scene. Neither of the images needs to be focused. In its generality, recovering the depth from defocused images is equivalent to the space-variant blur identification problem. Some of the important advantages of the DFD method are as follows.作者: Malfunction 時間: 2025-3-22 18:55 作者: GLEAN 時間: 2025-3-23 00:26 作者: 字形刻痕 時間: 2025-3-23 02:39 作者: obstinate 時間: 2025-3-23 09:00 作者: uveitis 時間: 2025-3-23 12:53
Recursive Computation of Depth from Multiple Images,tain . 1 independent estimates of the depth. The mean value of these estimates would give a reasonably robust estimate of the true depth. As the number of observations grows, one can expect the accuracy to further improve.作者: Urgency 時間: 2025-3-23 14:26
here a special lighting device is used for scene illumination. Passive methods have a wider range of applicability and also correspond to the way humans infer 3-D structure from visual images.978-1-4612-7164-2978-1-4612-1490-8作者: 難解 時間: 2025-3-23 18:42 作者: heartburn 時間: 2025-3-23 23:08
Depth Recovery from Defocused Images,image acquisition process under the assumption that all depths within a scene are in focus simultaneously. While the image through a pinhole camera model provides photometric information (i.e., scene radiance), it lacks geometric information (i.e., the distances of visible surfaces). However, practi作者: 前奏曲 時間: 2025-3-24 04:08 作者: Pantry 時間: 2025-3-24 08:14 作者: chance 時間: 2025-3-24 11:13 作者: 大廳 時間: 2025-3-24 17:27 作者: 事先無準(zhǔn)備 時間: 2025-3-24 19:17
MRF Model-Based Identification of Shift-Variant PSF, special case of the more general DFD problem in which the depth must be recovered given two defocused images of a scene. Although it is true that acquiring a focused image of a scene is a difficult task by itself, the problem addressed by Pentland [Pen87] is, nevertheless, quite interesting in its 作者: jarring 時間: 2025-3-25 00:36 作者: Intend 時間: 2025-3-25 04:12 作者: Ornithologist 時間: 2025-3-25 07:47 作者: 人充滿活力 時間: 2025-3-25 12:28 作者: 彈藥 時間: 2025-3-25 18:05
https://doi.org/10.1007/978-94-009-6475-4 blur is estimated by considering the defocusing process to be shift-invariant over that local region. However, each local region is analyzed independently to estimate the depth corresponding to that local region. But splitting an image into independent subimages introduces an error in the estimate 作者: 驚呼 時間: 2025-3-25 20:51
https://doi.org/10.1007/978-94-009-6475-4g the Fourier transform of a signal by a function ., the transfer function of the filter, to obtain a filtered version of the signal. For time-variant filtering, it is necessary to look for other representations that play a similar role to that of the Fourier transform in the time-invariant case. In作者: Triglyceride 時間: 2025-3-26 01:57 作者: arousal 時間: 2025-3-26 05:03 作者: 增減字母法 時間: 2025-3-26 09:33 作者: Adornment 時間: 2025-3-26 15:22 作者: 羽飾 時間: 2025-3-26 20:47 作者: MAUVE 時間: 2025-3-27 00:36
https://doi.org/10.1007/978-1-4612-1490-8Computer Vision; Markov Random Field; algorithms; autonom; filtering; image restoration; industrial robot; 作者: 高興一回 時間: 2025-3-27 02:35
978-1-4612-7164-2Springer Science+Business Media New York 1999作者: 走路左晃右晃 時間: 2025-3-27 09:05
https://doi.org/10.1007/978-94-009-6475-4In this chapter, we present brief mathematical reviews on time-frequency representations, the calculus of variations, and the Markov random field. These concepts have been used in later chapters in the depth recovery process. Readers familiar with these concepts may skip this chapter.作者: 含沙射影 時間: 2025-3-27 10:37
Mathematical Background,In this chapter, we present brief mathematical reviews on time-frequency representations, the calculus of variations, and the Markov random field. These concepts have been used in later chapters in the depth recovery process. Readers familiar with these concepts may skip this chapter.作者: Preamble 時間: 2025-3-27 14:10 作者: Alveoli 時間: 2025-3-27 21:31
http://image.papertrans.cn/d/image/265838.jpg作者: Vertebra 時間: 2025-3-27 23:53 作者: 幼稚 時間: 2025-3-28 04:51
Passive Methods for Depth Recovery,means that a view integration must be performed on multiple partial views of the object. Consequently, a great deal of interest has been generated amongst the computer vision and robotics research community in the acquisition of depth information. Humans use a great variety of vision-based passive d作者: COWER 時間: 2025-3-28 06:32 作者: 不可比擬 時間: 2025-3-28 10:35
MRF Model-Based Identification of Shift-Variant PSF,he space-variant blur by comparing the focused and the defocused image over local regions in which the blur is assumed to be constant Pen87. A window of appropriate size is moved over both the images by translating the window. At every position of the window, the estimate of the blur corresponding t作者: Suggestions 時間: 2025-3-28 17:12
Simultaneous Depth Recovery and Image Restoration,den [Fri72] developed a restoration formula based on the principle of maximum entropy. In [AJ78], Angel and Jain employ a conjugate gradient descent method for restoration of images degraded by spatially varying PSFs. Trussel et al. propose a method in which the image is partitioned into rectangular作者: Radiation 時間: 2025-3-28 21:19
https://doi.org/10.1007/978-94-009-6475-4means that a view integration must be performed on multiple partial views of the object. Consequently, a great deal of interest has been generated amongst the computer vision and robotics research community in the acquisition of depth information. Humans use a great variety of vision-based passive d作者: 殖民地 時間: 2025-3-29 00:52
https://doi.org/10.1007/978-94-009-6475-4acent patches of visible surfaces in the scene overlap on the image detector. The effect on the estimate of blur due to the image overlap problem can be reduced by choosing a larger size for the subimage. But it may not be always possible to choose a large enough local region owing to the depth vari作者: Mammal 時間: 2025-3-29 03:55
https://doi.org/10.1007/978-94-009-6475-4he space-variant blur by comparing the focused and the defocused image over local regions in which the blur is assumed to be constant Pen87. A window of appropriate size is moved over both the images by translating the window. At every position of the window, the estimate of the blur corresponding t作者: 有幫助 時間: 2025-3-29 07:45
https://doi.org/10.1007/978-94-009-6475-4den [Fri72] developed a restoration formula based on the principle of maximum entropy. In [AJ78], Angel and Jain employ a conjugate gradient descent method for restoration of images degraded by spatially varying PSFs. Trussel et al. propose a method in which the image is partitioned into rectangular作者: 針葉 時間: 2025-3-29 11:31
Depth From Defocus: A Real Aperture Imaging Approach作者: 瘋狂 時間: 2025-3-29 17:20
