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.

Highlights

  • Since the optical lens has limited depth of focus (DOF), it is difficult to obtain an image of an object with every part in the field focused

  • This paper provides an effective method for fusing various images by using Q-shift Dual Tree Complex Wavelet Transform (DTCWT)

  • Since fusion rule is another significant factor in image fusion, five different fusion rules are presented in this article and evaluated both visually and objectively

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Summary

Introduction

Since the optical lens has limited depth of focus (DOF), it is difficult to obtain an image of an object with every part in the field focused. The solution is to use multifocus image fusion to extract in-focus information from each partially focused image into one fully focused image, which is better for visual perception and further calculation. This technology has been extended to various fields, such as microscopic imaging, visual inspection, 3D shape recovery, and measurement [2]. We have proposed an effective fusion rule for multifocus image fusion after using Q-shift DTCWT and performed this method over partially focused image sequences blurred by Gaussian operators and microscopic image sequences.

Q-Shift DTCWT Related Theory
The Proposed Fusion Methods
Fusion Rules
Experimental Results and Analysis
Method
Part 1 Part 2 Part 3
Time Consumption
Conclusion
Full Text
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