Simultaneous HDR image reconstruction and denoising for dynamic scenes

Cecilia Aguerrebere           Julie Delon           Yann Gousseau           Pablo Musé          

Télécom ParisTech          IIE, U. de República

Input multi-exposure sequence (JPEG version)

HDR Result     Extracts showing no ghosting artifacts

Extracts showing no ghosting artifacts and denoising capacity

Abstract

High dynamic range (HDR) images are usually generated by combining multiple photographs acquired with different exposure times. This approach, while effective, suffers from various drawbacks. The irradiance estimation is performed by combining, for each pixel, different exposure values at the same spatial position. This estimation scheme does not take advantage of the redundancy present in most images. Moreover, images must be perfectly aligned and objects must be in the exact same position in all frames in order to combine the different exposures. In this work, we propose a new HDR image generation approach that simultaneously copes with these problems and exploits image redundancy to produce a denoised result. A reference image is chosen and a patch-based approach is used to find similar pixels that are then combined for the irradiance estimation. This patch-based approach permits to obtain a denoised result and is robust to image misalignments and object motions. Results show significant improvements in terms of noise reduction over previous HDR image generation techniques, while being robust to motion and changes between the exposures.

Paper

Full text (BibTeX) Slides (compressed) Slides (full)

Datasets (raw images) and Results

example1.tar.gz example2.tar.gz example3.tar.gz

Source code

nlhdr_v1.0.tar.gz (Error corrected in the "Usage example" in the README file!)

Matlab version (mex)

nlhdr_matlab.tar.gz

Matlab code to read/write Float EXR

matlabEXR.tar.gz