Description

The real world scenes have a very wide range of luminance levels. But in the field of photography, the ordinary cameras are not capable of capturing the true dynamic range of a natural scene. To enhance the dynamic range of the captured image, a technique known as High Dynamic Range (HDR) imaging is generally used. HDR imaging is the process of capturing scenes with larger intensity range than what conventional sensors can capture. It can faithfully capture the details in dark and bright part of the scene. In this paper HDR generation method such as multiple exposure fusion in image domain and radiance domain are reviewed. The main issues in HDR imaging using multiple exposure combination technique are Misalignment of input images, Noise in data sets and Ghosting artefacts. In the existing system, there are various methods in which the camera and local motion are compensated to eliminate ghosting effect. In this project the system proposed a high dynamic range (HDR) image generation method using a single input image. The proposed approach computes an adaptive weight for each image to improve HDR performance. Additionally, contrast limited adaptive histogram equalization (CLAHE) is utilized to improve overall appearance of the HDR image in local dark and bright regions. Adaptive histogram equalization (AHE) is a method for local contrast enhancement and it is an extension to the traditional histogram equalization technique. AHE simply partitions the image into non-overlapping regions and applies histogram equalization to each sub-region in order to redefine the pixel values of the image. The low computational complexity of the proposed approach makes it suitable for smart phones and compact consumer cameras.