Abstract
Abstract. This paper proposes a method to estimate the local sharpness of an optical system through the wavelet-based analysis of a large set of images it acquired. Assuming a space-invariant distribution of image features, such as in the aerial photography context, the proposed approach produces a sharpness map of the imaging device over 16 × 16 pixels blocks that enables, for instance, the detection of optical defects and the qualification of the mosaicking of multiple sensor images into a larger composite image. The proposed analysis is based on accumulating of the edge maps corresponding to the first levels of the Haar Transform of each image of the dataset, following the intuition that statistically, each pixel will see the same image structures. We propose a calibration method to transform these accumulated edge maps into a sharpness map by approximating the local PSF (Point Spread Function) with a Gaussian blur.
Highlights
Characterizing the spatial resolution of an imaging system is an important field of image processing and is used for assessing its image quality and for restoration purposes.This characterization can be obtained by shooting some perfectly known objects, preferably periodic patterns such as Foucault resolution targets or Siemens stars (Fleury and Mathieu, 1956) to deduce the smallest periodic detail discernible by the system through the determination of a Modular Transfer Function (MTF) (Becker et al, 2007)
The second visible artifact is the vertical line in the middle of the figure: the decrease in sharpness in this part of the imaging system may come from the seam between the left and right images
Our work aims at quantifying the amount of blur induced by an optical system from a large set of images that it has acquired
Summary
Characterizing the spatial resolution of an imaging system is an important field of image processing and is used for assessing its image quality and for restoration purposes This characterization can be obtained by shooting some perfectly known objects, preferably periodic patterns such as Foucault resolution targets or Siemens stars (Fleury and Mathieu, 1956) to deduce the smallest periodic detail discernible by the system through the determination of a Modular Transfer Function (MTF) (Becker et al, 2007). Some imaging systems (mounted with fisheye lenses for instance) show a very space-dependent resolution In these circumstances, a local study is more suitable and can be done by using a wall of targets, such as Siemens stars (Kedzierski, 2008). Our contribution is twofold: we overcomes this limitation by extending Tong’s method (designed for a single image) to a large set of images, and we propose a quantitative characterization of sharpness through a blur radius
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
