A focus profile depicts the image sharpness (or focus value) as the lens sweeps along the optical axis of a camera. Accurate modeling of the focus profile is important to many imaging tasks. In this paper, we present an approach to focus profile modeling that makes the search of in-focus lens position a mathematically tractable problem, and hereby improves the efficiency and accuracy of image acquisition. The proposed approach entails a transformation that converts the representation of a focus profile to quadratic form. An important feature of the approach is that no prior knowledge of the focus measurement technique is required. Experimental results are provided to demonstrate the effectiveness of the approach.

A focus profile model is used to estimate the in-focus lens position so that a sharp image or video can be captured. In this paper, we propose an approach that transforms a wide variety of focus profiles generated by different focus measurement techniques into an analytic form and thereby converts the search of in-focus lens position into a mathematically tractable problem, resulting in a wide effective range and efficient image acquisition. An important feature of the approach is that it does not require any knowledge of the focus measurement technique used in a camera. Experimental results, including demo videos, are provided to demonstrate the effectiveness of the approach.

For a video camera to continuously focus on a moving object in the autofocus process, accurate estimate of the in-focus lens position is required in order to avoid the so-called bouncing phenomenon that is resulted from back-and-forth lens movements around the in-focus lens position. In this paper, we present a novel continuous focus method that effectively improves the accuracy of in-focus lens position estimate for dynamic scenes by a Kalman filter and provides good user experience by a smooth control of the lens movements in the autofocus process. Experimental results are shown to demonstrate the performance of our method.

A focus profile having a steeper peak is more resistant to image noise in the autofocus (AF) process of a digital camera. However, a focus profile of such shape normally has a flatter out-of-focus region on either side of the profile, resulting in a slow AF process due to the lack of clue about where the lens should move when the lens is in such regions. To address the problem, we provide a statistical analysis of the focus profile and show that a strictly monotonic transformation of the focus profile preserves the accuracy of the AF. On the basis of this analysis, we propose a new focus profile representation that transforms the focus profile to the reciprocal domain in which the reciprocal focus profile is modeled by a polynomial function. This transformation makes the AF mathematically tractable and boosts the search speed. Experimental results are shown to demonstrate the advantage of the proposed representation.

In this paper, we propose a new autofocus approach that transforms the focus profile to the reciprocal domain. A key feature of this approach is that it makes the autofocus process mathematically tractable in both in-focus and out-of- focus regions, thereby allowing a digital camera or camcorder to expedite the search of the best lens position for capturing the image that has the maximum focus value. Experimental results are provided to illustrate the advantage of the proposed approach.