A high dynamic range imaging algorithm: implementation and evaluation

Abstract

Camera specifications have become smaller and smaller, accompanied with great strides in technology and thinner product demands, which have led to some challenges and problems. One of those problems is that the image quality is reduced at the same time. The decrement of radius lens is also a cause leading to the sensor not absorbing a sufficient amount of light, resulting in captured images which include more noise. Moreover, current image sensors cannot preserve whole dynamic range in the real world. This paper proposes a Histogram Based Exposure Time Selection (HBETS) method to automatically adjust the proper exposure time of each lens for different scenes. In order to guarantee at least two valid reference values for High Dynamic Range (HDR) image processing, we adopt the proposed weighting function that restrains random distributed noise caused by micro-lens and produces a high quality HDR image. In addition, an integrated tone mapping methodology, which keeps all details in bright and dark parts when compressing the HDR image to Low Dynamic Range (LDR) image for display on monitors, is also proposed. Eventually, we implement the entire system on Adlink MXC-6300 platform that can reach 10 fps to demonstrate the feasibility of the proposed technology.