<title>Fast auto-exposure algorithm based on numerical analysis</title>

Abstract

In this paper, we propose a new scene-adaptive exposure control algorithm for digital still camera to achieve fast convergence to targeted average luminance level. We focus especially on an electrical shutter control method, which enables the widest range of control. We tested to find out the relationship between the electrical shutter sped, which is decided by the number of reset pulses of CCD, and the luminance. We composed various luminance environments and generated the exposure data of every combination of luminance environments and the number of reset pulses. We obtained the relationship that as increasing the number of reset pulses, the average luminance level of the captured image decreases. The method that we propose is the Secant Method, one of iteration method and we use it for fast and stable convergence to targeted luminance level. On the plane whose axes are average luminance value and the number of reset pulses, a straight line is defined by two points. One point is computed from the image captured at t0. Another point has minimum luminance value under the assumption that maximum reset pulses cause minimum luminance value 0. The new shutter sped on the straight line makes a new point t1. By repeating this, we can find the targeted luminance stable and fast.