Ghosting-free multi-exposure image fusion in gradient domain

This paper presents an algorithm to produce ghosting-free High Dynamic Range (HDR) image by fusing set of multiple exposed images in gradient domain. Recently proposed Gradient domain based exposure fusion method provides high quality result but the scope of which is limited to static camera without foreground object motion. The presence of moving objects/hand shake produces a set of misaligned images. The result of gradient domain approach on misaligned images suffers from ghosting artifacts. In order to produce better HDR image without image registration, we propose to create an aligned image set from input image set by photometric calibration. The gradient of aligned image set is then used to reconstruct the fused final image. The proposed algorithm tested on several publicly available dynamic image sets shows that resultant HDR image is ghosting-free and well exposed. Additionally, the proposed method is fast and thus can be used in consumer appliances such as mobile phones, portable devices with digital cameras.

[1]  Shree K. Nayar,et al.  Determining the Camera Response from Images: What Is Knowable? , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Ning He,et al.  Exposure fusion based on sparse representation using approximate K-SVD , 2014, Neurocomputing.

[3]  Yung-Yu Chuang,et al.  High dynamic range image reconstruction from hand-held cameras , 2009, CVPR.

[4]  Eli Shechtman,et al.  Robust patch-based hdr reconstruction of dynamic scenes , 2012, ACM Trans. Graph..

[5]  Ramakrishna Kakarala,et al.  A method for fusing a pair of images in the JPEG domain , 2011, Journal of Real-Time Image Processing.

[6]  Panajotis Agathoklis,et al.  A wavelet based method for image reconstruction from gradient data with applications , 2013, Multidimensional Systems and Signal Processing.

[7]  Panajotis Agathoklis,et al.  Multi-Exposure and Multi-Focus Image Fusion in Gradient Domain , 2016, J. Circuits Syst. Comput..

[8]  Hiroshi Nagahashi,et al.  Cross-Parameterization for Triangular Meshes with Semantic Features , 2007 .

[9]  Yu Liu,et al.  Dense SIFT for ghost-free multi-exposure fusion , 2015, J. Vis. Commun. Image Represent..

[10]  Chiou-Ting Hsu,et al.  Alignment-free exposure fusion of image pairs , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[11]  Wai-kuen Cham,et al.  Reference-guided exposure fusion in dynamic scenes , 2012, J. Vis. Commun. Image Represent..

[12]  Steve Mann,et al.  Comparametric equations with practical applications in quantigraphic image processing , 2000, IEEE Trans. Image Process..

[13]  Ioannis Andreadis,et al.  Multi-Exposure Image Fusion based on Illumination Estimation , 2011 .

[14]  Jan Kautz,et al.  Exposure Fusion , 2007, 15th Pacific Conference on Computer Graphics and Applications (PG'07).