DCT-Based HDR Exposure Fusion Using Multiexposed Image Sensors

It is difficult to apply existing exposure methods to a resource-constrained platform. their pyramidal image processing and quality measures for interesting areas that need to be preserved require a lot of time and memory. the work presented in this paper is a dct-based hdr exposure fusion using multiexposed image sensors. in particular,it uses the quantization process in jpeg encoding as a measurement of image quality such that the fusion process can be included in the dct-based compression baseline. to enhance global image luminance,a gauss error function based on camera characteristics is presented. in the simulation,the proposed method yields good quality images,which balance naturalness and object identification. this method also requires less time and memory. this qualifies our technique for use in resource-constrained platforms. © 2017 geun-young lee et al.