Robust Depth-from-Defocus for Autofocusing in the Presence of Image Shifts

نویسندگان

  • Younsik Kang
  • Xue Tu
  • Satyaki Dutta
  • Murali Subbarao
چکیده

A new passive ranging technique named Robust Depth-from-Defocus (RDFD) is presented for autofocusing in digital cameras. It is adapted to work in the presence of image shift and scale change caused by camera/hand/object motion. RDFD is similar to spatial-domain Depth-from-Defocus (DFD) techniques in terms of computational efficiency, but it does not require pixel correspondence between two images captured with different defocus levels. It requires approximate correspondence between image regions in different image frames as in the case of Depth-from-Focus (DFF) techniques. Theory and computational algorithm are presented for two different variations of RDFD. Experimental results are presented to show that RDFD is robust against image shifts and useful in practical applications. RDFD also provides insight into the close relation between DFF and DFD techniques.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Investigation of a Localized Approach to Shift-Variant Image Restoration and Robust Autofocusing

of the Dissertation Investigation of a Localized Approach to Shift-Variant Image Restoration and Robust Autofocusing by Younsik Kang Doctor of Philosophy in Electrical Engineering Stony Brook University 2011 Images of three-dimensional (3D) scenes or dynamic scenes captured by a digital camera are in general blurred by different degrees at different points in the image. The blur level at a pixe...

متن کامل

Enhanced Depth from Defocus Estimation: Tolerance to Spatial Displacements

Most existing depth from defocus techniques assume that spatial shifts between a pair of images of the same scene are negligible. In practical computer vision, making sure that there is no displacements is difficult. Such an assumption may thus lead to a lack of accuracy. This paper presents an algorithm for an estimation of depth from defocus blur from two images which is tolerant to spatial s...

متن کامل

Single-frame rapid autofocusing for brightfield and fluorescence whole slide imaging.

A critical consideration for whole slide imaging (WSI) platform is to perform accurate autofocusing at high speed. Typical WSI systems acquire a z-stack of sample images and determine the best focal position by maximizing a figure of merit. This strategy, however, has suffered from several limitations, including low speed due to multiple image acquisitions, relatively low accuracy of focal plan...

متن کامل

Performance Evaluation of Different Depth From Defocus (DFD) Techniques

In this paper, several binary mask based Depth From Defocus (DFD) algorithms are proposed to improve autofocusing performance and robustness. A binary mask is defined by thresholding image Laplacian to remove unreliable points with low Signal-to-Noise Ratio (SNR). Three different DFD schemes-with/without spatial integration and with/without squaring-are investigated and evaluated, both through ...

متن کامل

Camera Calibration and Performance Evaluation of Depth From Defocus (DFD)

Real-time and accurate autofocusing of stationary and moving objects is an important problem in modern digital cameras. Depth From Defocus (DFD) is a technique for autofocusing that needs only two or three images recorded with different camera parameters. In practice, there exist many factors that affect the performance of DFD algorithms, such as nonlinear sensor response, lens vignetting, and ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009