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Related papers: Analysis of Magnification in Depth from Defocus

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The two-sensor depth from defocus (DFD) technique for the measurement of drop sizes in a spray is further developed to achieve higher spatial and temporal resolution, to improve estimates of size and number concentration, and to provide…

Macro lens has the advantages of high resolution and large magnification, and 3D modeling of small and detailed objects can provide richer information. However, defocus blur in macrophotography is a long-standing problem that heavily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Yifan Zhao , Liangchen Li , Yuqi Zhou , Kai Wang , Yan Liang , Juyong Zhang

Depth-from-focus (DFF) is a technique that infers depth using the focus change of a camera. In this work, we propose a convolutional neural network (CNN) to find the best-focused pixels in a focal stack and infer depth from the focus…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Fengting Yang , Xiaolei Huang , Zihan Zhou

Multi-focus image fusion (MFF) is a popular technique to generate an all-in-focus image, where all objects in the scene are sharp. However, existing methods pay little attention to defocus spread effects of the real-world multi-focus…

Computer Vision and Pattern Recognition · Computer Science 2021-02-02 Shuang Xu , Lizhen Ji , Zhe Wang , Pengfei Li , Kai Sun , Chunxia Zhang , Jiangshe Zhang

We show that the errors due to atmospheric refraction are present in the magnitudes determined with the Difference Images Analysis method. In case of single, unblended stars the size of the effect agrees with the theoretical prediction. But…

Astrophysics · Physics 2007-05-23 A. Kruszewski , I. Semeniuk

Estimating relative camera poses between images has been a central problem in computer vision. Methods that find correspondences and solve for the fundamental matrix offer high precision in most cases. Conversely, methods predicting pose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-06 Chris Rockwell , Nilesh Kulkarni , Linyi Jin , Jeong Joon Park , Justin Johnson , David F. Fouhey

NeRF acquisition typically requires careful choice of near planes for the different cameras or suffers from background collapse, creating floating artifacts on the edges of the captured scene. The key insight of this work is that background…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Julien Philip , Valentin Deschaintre

It has long been an ill-posed problem to predict absolute depth maps from single images in real (unseen) indoor scenes. We observe that it is essentially due to not only the scale-ambiguous problem but also the focal-ambiguous problem that…

Computer Vision and Pattern Recognition · Computer Science 2023-07-28 Chengrui Wei , Meng Yang , Lei He , Nanning Zheng

Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios. However, in most real-world images, blur is caused by different factors, e.g., motion and defocus.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Kaihao Zhang , Tao Wang , Wenhan Luo , Boheng Chen , Wenqi Ren , Bjorn Stenger , Wei Liu , Hongdong Li , Ming-Hsuan Yang

The extended source effect on microlensing magnification is non-negligible and must be taken into account for in an analysis of microlensing. However, the evaluation of the extended source magnification is numerically expensive because it…

Instrumentation and Methods for Astrophysics · Physics 2022-10-05 Sunao Sugiyama

3D Time-of-Flight camera's images are affected by errors due to the diffuse (indirect) light and to the flare light. The presented method improves the 3D image reducing the distance's errors to dark surface objects. This is achieved by…

Computer Vision and Pattern Recognition · Computer Science 2009-10-01 D. Falie

Image de-blurring is important in many cases of imaging a real scene or object by a camera. This project focuses on de-blurring an image distorted by an out-of-focus blur through a simulation study. A pseudo-inverse filter is first explored…

Computer Vision and Pattern Recognition · Computer Science 2017-11-03 Yuzhen Lu

Extracting depth information from photon-limited, defocused images is challenging because depth from defocus (DfD) relies on accurate estimation of defocus blur, which is fundamentally sensitive to image noise. We present a novel approach…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Wei Xu , Charles James Wagner , Junjie Luo , Qi Guo

Speckle photography can be used to monitor deformations of solid surfaces. The measuring characteristics, such as range or lateral resolution depend heavily on the optical recording and illumination set-up. This paper shows how, by the…

Optics · Physics 2014-01-30 Jose M. Diazdelacruz

Image frames obtained in darkness are special. Just multiplying by a constant doesn't restore the image. Shot noise, quantization effects and camera non-linearities mean that colors and relative light levels are estimated poorly. Current…

Computer Vision and Pattern Recognition · Computer Science 2022-06-06 Sara Aghajanzadeh , David Forsyth

This paper demonstrates a practical method that can correct spatial varying blur from a set of images of the same object. The algorithm jointly estimates the object and local point spread functions~(PSF). The method prioritizes sections…

Image and Video Processing · Electrical Eng. & Systems 2020-11-04 Wouter van de Ketterij , Oleg Soloviev , Michel Verhaegen

There is an increasing interest in using image-generating diffusion models for deep data augmentation and image morphing. In this context, it is useful to interpolate between latents produced by inverting a set of input images, in order to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Erik Landolsi , Fredrik Kahl

An image captured with a wide-aperture camera exhibits a finite depth-of-field, with focused and defocused pixels. A compact and robust representation of focus and defocus helps analyze and manipulate such images. In this work, we study the…

Computer Vision and Pattern Recognition · Computer Science 2020-12-22 Parikshit Sakurikar , P. J. Narayanan

Real camera footage is subject to noise, motion blur (MB) and depth of field (DoF). In some applications these might be considered distortions to be removed, but in others it is important to model them because it would be ineffective, or…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Siddhant Prakash , David R. Walton , Rafael K. dos Anjos , Anthony Steed , Tobias Ritschel

Precise calibration is a must for high reliance 3D computer vision algorithms. A challenging case is when the camera is behind a protective glass or transparent object: due to refraction, the image is heavily distorted; the pinhole camera…

Computer Vision and Pattern Recognition · Computer Science 2019-09-25 Szabolcs Pável , Csanád Sándor , Lehel Csató