![]() ![]() In this method, each input image is decomposed into a Laplace pyramid and a Gauss pyramid of weight map is established for each image according to contrast, saturation, and exposure, thus realizing a multi-resolution fusion framework. Since tone mapping is time-consuming and requires many steps to complete, it limits the applicability of this method.Įxposure fusion was first proposed by Mertens et al. In addition, after the HDR image is acquired, the range of the HDR image is compressed using hue mapping to make it display on the monitor. However, this approach is difficult to determine the CRF because researchers need to calculate the CRF each time they change the capturing device or adjust the parameters (exposure time, IOS, etc.). In the early stage of development, many researchers proposed an HDR generation scheme to solve this problem using the camera response function (CRF) and the exposure time information of the input image to linearly map the pixel value of the scene brightness to generate HDR images in line with the visual quality. Low dynamic range images taken with mobile phones and cameras cannot accurately reflect the dynamic range of the real world, mainly because the image sensors in mobile phones and cameras have limited response to the dynamic range of natural light, so they cannot capture all the details of the light and dark areas in the dynamic scene. ![]() For the past few decades, generating high dynamic range (HDR) images from a group of low dynamic range (LDR) images with different exposures has been a challenge. ![]()
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