학술논문

Multi-scale exposure fusion via gradient domain guided image filtering
Document Type
Conference
Source
2017 IEEE International Conference on Multimedia and Expo (ICME) Multimedia and Expo (ICME), 2017 IEEE International Conference on. :1105-1110 Jul, 2017
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Image edge detection
Smoothing methods
Laplace equations
Dynamic range
Algorithm design and analysis
Image color analysis
Fuses
Exposure fusion
image pyramid
gradient domain guided image filter
edge-preserving smoothing
high dynamic range
Language
ISSN
1945-788X
Abstract
Multi-scale exposure fusion is an efficient way to fuse differently exposed low dynamic range (LDR) images of a high dynamic range (HDR) scene into a high quality LDR image directly. It can produce images with higher quality than single-scale exposure fusion, but has a risk of producing halo artifacts and cannot preserve details in brightest or darkest regions well in the fused image. In this paper, an edge-preserving smoothing pyramid is introduced for the multi-scale exposure fusion. Benefiting from the edge-preserving property of the filter used in the algorithm, the details in the brightest/darkest regions are preserved well and no halo artifacts are produced in the fused image. The experimental results prove that the proposed algorithm produces better fused images than the state-of-the-art algorithms both qualitatively and quantitatively.