Single shot High Dynamic Range imaging using histogram separation and exposure fusion

Abstract

Conventionally, High Dynamic Range (HDR) images are generated by fusing multiple exposure Low Dynamic Range (LDR) images, where the HDR output often suffers from artifacts due to misalignment of camera and presence of dynamic objects in the scene. An efficient approach to overcome these issues is to use single shot HDR imaging. In this paper, we propose a method for generating an HDR image from a single LDR image. We first generate multiple exposures of the given scene using histogram separation by adopting varying bin sizes. The resulting LDR images are fused making use of the quality measures such as contrast, saturation and well -exposedness. The results show the effectiveness of the proposed approach which is verified qualitatively and in terms of various quantitative measures.

Software-Defined Imaging: A Survey

“…In [104], a deep optical-based HDR imaging approach was proposed, where the encoder is modeled by the point spread function of the leans and the decoder is parameterized by a convolutional neural network (CNN). Similarly, other works of research are available in the literature, which performs single-shot HDR imaging [105], [106], [107], [108]. Very recently, a novel algorithm has been proposed for rendering single-shot HDR images by exploiting quantization noise information [109].…”