Multifocus Image Fusion in Q-Shift DTCWT Domain Using Various Fusion Rules

Yingzhong Tian, Jie Luo, Wenjun Zhang, Tinggang Jia, Aiguo Wang and Long Li

Mathematical Problems in Engineering, 2016, vol. 2016, 1-12

Abstract:

Multifocus image fusion is a process that integrates partially focused image sequence into a fused image which is focused everywhere, with multiple methods proposed in the past decades. The Dual Tree Complex Wavelet Transform (DTCWT) is one of the most precise ones eliminating two main defects caused by the Discrete Wavelet Transform (DWT). Q-shift DTCWT was proposed afterwards to simplify the construction of filters in DTCWT, producing better fusion effects. A different image fusion strategy based on Q-shift DTCWT is presented in this work. According to the strategy, firstly, each image is decomposed into low and high frequency coefficients, which are, respectively, fused by using different rules, and then various fusion rules are innovatively combined in Q-shift DTCWT, such as the Neighborhood Variant Maximum Selectivity (NVMS) and the Sum Modified Laplacian (SML). Finally, the fused coefficients could be well extracted from the source images and reconstructed to produce one fully focused image. This strategy is verified visually and quantitatively with several existing fusion methods based on a plenty of experiments and yields good results both on standard images and on microscopic images. Hence, we can draw the conclusion that the rule of NVMS is better than others after Q-shift DTCWT.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:5637306

DOI: 10.1155/2016/5637306

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