Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-Focus Image Fusion based on Gradient Transform   Multi-focus image fusion is a challenging field of study that aims to provide
a completely focused image by integrating focused and un-focused pixels. Most
existing methods suffer from shift variance, misregistered images, and
data-dependent. In this study, we introduce a novel gradient information-based
multi-focus image fusion method that is robust for the aforementioned problems.
The proposed method first generates gradient images from original images by
using Halftoning-Inverse Halftoning (H-IH) transform. Then, Energy of Gradient
(EOG) and Standard Deviation functions are used as the focus measurement on the
gradient images to form a fused image. Finally, in order to enhance the fused
image a decision fusion approach is applied with the majority voting method.
The proposed method is compared with 17 different novel and conventional
techniques both visually and objectively. For objective evaluation, 6 different
quantitative metrics are used. It is observed that the proposed method is
promising according to visual evaluation and 83.3% success is achieved by being
first in five out of six metrics according to objective evaluation.

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The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th