HDR-Like Image from Pseudo-Exposure Image Fusion: A Genetic Algorithm Approach
Shantanu Sen Gupta, Shifat Hossain, Ki‐Doo Kim
Abstract
Image distortion during multiple-exposure capture is a common scenario, and most of the existing legacy image content is in the low dynamic range (LDR). For both of these problems, pseudo multiple exposure image generation from a single image is a possible solution. Hence, in this article, we propose a novel method for high dynamic range (HDR)-like image generation by fusing pseudo-multi-exposure images that are produced from only one single image. The proposed pseudo-exposure image generation method is based on intensity mapping function (IMF). First, our system learns the relation between different exposure images with the help of genetic algorithm and generates long and short exposure images. In the second step, we fuse images with different exposures to generate the HDR-like image. Our method outperforms several inverse tone mapping operator (ITMO)-based methods. The simplicity and good performance of the proposed method makes it suitable for mobile phones and other consumer electronics. We also develop a demo software to validate the proposed method.