Paper
3 March 2008 Fast and accurate auto focusing algorithm based on two defocused images using discrete cosine transform
Author Affiliations +
Proceedings Volume 6817, Digital Photography IV; 68170D (2008) https://doi.org/10.1117/12.766253
Event: Electronic Imaging, 2008, San Jose, California, United States
Abstract
This paper describes the new method for fast auto focusing in image capturing devices. This is achieved by using two defocused images. At two prefixed lens positions, two defocused images are taken and defocused blur levels in each image are estimated using Discrete Cosine Transform (DCT). These DCT values can be classified into distance from the image capturing device to main object, so we can make distance vs. defocused blur level classifier. With this classifier, relation between two defocused blur levels can give the device the best focused lens step. In the case of ordinary auto focusing like Depth from Focus (DFF), it needs several defocused images and compares high frequency components in each image. Also known as hill-climbing method, the process requires about half number of images in all focus lens steps for focusing in general. Since this new method requires only two defocused images, it can save lots of time for focusing or reduce shutter lag time. Compared to existing Depth from Defocus (DFD) which uses two defocused images, this new algorithm is simple and accurate as DFF method. Because of this simplicity and accuracy, this method can also be applied to fast 3D depth map construction.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Byung-Kwan Park, Sung-Su Kim, Dae-Su Chung, Seong-Deok Lee, and Chang-Yeong Kim "Fast and accurate auto focusing algorithm based on two defocused images using discrete cosine transform", Proc. SPIE 6817, Digital Photography IV, 68170D (3 March 2008); https://doi.org/10.1117/12.766253
Lens.org Logo
CITATIONS
Cited by 12 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Cameras

Atrial fibrillation

Neurons

Image processing

Line edge roughness

Neural networks

Camera shutters

RELATED CONTENT

The use of machine learning algorithms for image recognition
Proceedings of SPIE (February 11 2020)
A color correction method in uniform color space
Proceedings of SPIE (November 05 2020)
Video measurements for forest inventory
Proceedings of SPIE (December 22 2000)
Research on image autofocus system based on neural network
Proceedings of SPIE (September 02 2003)
Development of an automated system for the analysis of print...
Proceedings of SPIE (September 07 1998)

Back to Top