Focus error estimation in images

Abstract

Estimating focus error in an image involves a training phase and an application phase. In the training phase, an optical system is represented by a point-spread function. An image sensor array is represented by one or more wavelength sensitivity functions, one or more noise functions, and one or more spatial sampling functions. The point-spread function is applied to image patches for each of multiple defocus levels within a specified range to produce training data. Each of the images for each defocus level (i.e. focus error) is sampled using the wavelength sensitivity and spatial sampling functions. Noise is added using the noise functions. The responses from the sensor array to the training data are used to generate defocus filters for estimating focus error within the specified range. The defocus filters are then applied to the image patches of the training data and joint probability distributions of filter responses to each defocus level are characterized. In the application phase, the filter responses to arbitrary image patches are obtained and combined to derive continuous, signed estimates of the focus error of each arbitrary image patch.

Description

[0001] Cross References to Related Applications [0002] This application is a co-pending non-provisional patent application with US Provisional Application No. 61 / 446566 filed on February 25, 2011, entitled "Defocus Estimation in a Single Natural Image". This provisional application is hereby expressly incorporated by reference in its entirety for all purposes. [0003] Statement Concerning Rights to Inventions Made in Federally Sponsored Research or Scientific Research [0004] The United States Government may have certain rights in this invention under the terms of National Institutes of Health Grant No. 2R01EY11747. technical field [0005] The present invention relates to autofocus optical systems, and more particularly to the estimation of errors in images received by the optical system. Background technique [0006] Autofocus optical systems (eg, digital still cameras, digital cameras, microscopes, microfabrication equipment) use sensors, control systems, and motors...

AI Technical Summary

Problems solved by technology

Although the phase detection method is faster, more accurate and estimates the defocus sign, it is expensive to implement because it requires special beam splitters, mirrors, prisms and sensors

Also, additional hardware increases the size and weight of the optical system

Also, this method does not work in "live view" mode (feature that allows the display of an optical system such as that of a digital camera to be used as a viewfinder)

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