NDLI: Analysis and design of coded apertures for defocus deblurring based on imaging system properties and optical features

Content Provider	IET Digital Library
Author	Masoudifar, Mina Pourreza, Hamid Reza
Abstract	As the physical size of single pixels in digital cameras grows smaller, the captured images are increasingly affected by defocused blurring and consequently valuable details are lost. Different aperture patterns have already been proposed to mitigate this problem based on presumed conditions, which maybe violated in practise. Sensor characteristics and current photometric scene properties have been largely ignored in the design of aperture patterns in the literature. In this study, a number of perceptually optimised coded apertures are introduced for defocused deblurring. These apertures are specifically designed considering illumination conditions, sensor specifications and human visual system characteristics. The designed patterns are compared with circular apertures of equal throughput and pinhole aperture. Experiments show signal-to-noise ratio (SNR) gains of up to 0.35 and 2 dB over circular and pinhole apertures, respectively. To study the trade-off between diffraction and deblurring gains, the proposed binary masks are enhanced by smoothing and morphological operations, which can yield non-binary and rounded binary patterns. The results of the authors’ study show that rounded binary patterns improve diffraction behaviour while maintaining the desired SNR level.
Starting Page	1123
Ending Page	1134
Page Count	12
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 12, Dec (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2015.0831
Journal	IET Image Processing
Publisher Date	2017-03-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Aperture Pattern Design Binary Masks Coded Aperture Analysis Coded Aperture Design Computer Vision And Image Processing Technique Current Photometric Scene Property Deblurring Gain Defocused Deblurring Diffraction Gain Digital Cameras Human Visual System Characteristic Illumination Condition Image Capture Image Processing Image Restoration Imaging System Property Light Diffraction Morphological Operation Natural Scenes Nonbinary Pattern Optical Feature Optical Image Optical, Image And Video Signal Processing Perceptually Optimised Coded Apertures Photometry Restoration Rounded Binary Pattern Sensor Characteristic Sensor Specifications Signal to Noise Ratio Smoothing Operation SNR Gain
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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