Information-Theoretic Channel for Multi-exposure Image Fusion

Abstract Multi-exposure image fusion has emerged as an increasingly important and interesting research topic in information fusion. It aims at producing with high quality by fusing a set of differently exposed images. In this article, we present pixel-level method for multi-exposure based on information-theoretic approach. our scheme, channel between two source images is used to compute the Rényi entropy associated each pixel one respect other hence produce weight maps Since direct weight-averaging introduce unpleasing artifacts, employ Laplacian multi-scale Based pyramid every scale are fused maps, final inversely reconstructed. proposed easy construct implement can deliver, less than second three input size 512$\times $340, competitive compelling results versus state-of-art methods through visual comparison objective evaluation.