TITLE:
Efficient Compressive Multi-Focus Image Fusion
AUTHORS:
Chao Yang, Bin Yang
KEYWORDS:
Clarity Measures, Compressive Imaging, Multi-Focus Image Fusion
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.9,
July
11,
2014
ABSTRACT: Two key points of
pixel-level multi-focus image fusion are the clarity measure and the pixel
coeffi- cients fusion rule. Along with different improvements on these two
points, various fusion schemes have been proposed in literatures. However, the traditional
clarity measures are not designed for compressive imaging measurements which
are maps of source sense with random or likely ran- dom measurements matrix. This
paper presents a novel efficient multi-focus image fusion frame- work for
compressive imaging sensor network. Here the clarity measure of the raw
compressive measurements is not obtained from the random sampling data itself
but from the selected Hada- mard coefficients which can also be acquired from
compressive imaging system efficiently. Then, the compressive measurements with
different images are fused by selecting fusion rule. Finally, the block-based
CS which coupled with iterative projection-based reconstruction is used to re- cover
the fused image. Experimental results on common used testing data demonstrate
the effectiveness of the proposed method.