• Neeruganti Vikram Teja
• P Vamsi
• Neelima K
• Nune Divya

This paper projects a new multi-scale exposure fusion algorithm to merge differently exposed low dynamic range (LDR) images by using the weighted guided image filter (WGIF) to smooth the Gaussian pyramids of weight maps. In the fused image, the details in the brightest and darkest regions of the HDR scene are preserved better without any change in relative brightness. Also a new weighted structure tensor is considered to the differently exposed images for enhanced detail extraction according to the preference. The proposed multi-scale exposure fusion algorithm with filter is suitable for a simple single image brightening algorithm for both low-light imaging and back-light imaging. The proposed algorithm yields better images for human perception. The results are compared for various parameters and the proposed design is found to be a better choice of processing the Multi-Scale Exposure images fusion due to better parameter values of standard deviation and entropy.

"Multi-scale Exposure Fusion for Low Dynamic Range Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.c729-c737, August-2022, Available :http://www.jetir.org/papers/JETIR2208277.pdf

"Multi-scale Exposure Fusion for Low Dynamic Range Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppc729-c737, August-2022, Available at : http://www.jetir.org/papers/JETIR2208277.pdf