Journal ArticleDOI
Boundary finding based multi-focus image fusion through multi-scale morphological focus-measure
Yu Zhang,Xiangzhi Bai,Tao Wang +2 more
TLDR
This paper proposes a novel boundary finding based multi-focus image fusion algorithm, in which the task of detecting the focused regions is treated as finding the boundaries between the focused and defocused regions from the source images.About:Â
This article is published in Information Fusion.The article was published on 2017-05-01. It has received 196 citations till now. The article focuses on the topics: Image fusion.read more
Citations
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Journal ArticleDOI
Multi-focus image fusion with a deep convolutional neural network
TL;DR: A new multi-focus image fusion method is primarily proposed, aiming to learn a direct mapping between source images and focus map, using a deep convolutional neural network trained by high-quality image patches and their blurred versions to encode the mapping.
Journal ArticleDOI
IFCNN: A general image fusion framework based on convolutional neural network
TL;DR: The experimental results show that the proposed model demonstrates better generalization ability than the existing image fusion models for fusing various types of images, such as multi-focus, infrared-visual, multi-modal medical and multi-exposure images.
Journal ArticleDOI
Deep learning for pixel-level image fusion: Recent advances and future prospects
TL;DR: This survey paper presents a systematic review of the DL-based pixel-level image fusion literature, summarized the main difficulties that exist in conventional image fusion research and discussed the advantages that DL can offer to address each of these problems.
Journal ArticleDOI
Pixel Convolutional Neural Network for Multi-Focus Image Fusion
TL;DR: Experimental results demonstrate that the proposed p-CNN is competitive with or even outperforms the state-of-the-art methods in terms of both subjective visual perception and objective evaluation metrics.
Journal ArticleDOI
Medical Image Fusion via Convolutional Sparsity Based Morphological Component Analysis
TL;DR: Experimental results demonstrate that the proposed CS-MCA model can outperform some benchmarking and state-of-the-art SR-based fusion methods in terms of both visual perception and objective assessment.
References
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Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Journal ArticleDOI
Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Journal ArticleDOI
Normalized cuts and image segmentation
Jianbo Shi,Jitendra Malik +1 more
TL;DR: This work treats image segmentation as a graph partitioning problem and proposes a novel global criterion, the normalized cut, for segmenting the graph, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups.
Journal ArticleDOI
Scale-space and edge detection using anisotropic diffusion
Pietro Perona,Jitendra Malik +1 more
TL;DR: A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced, chosen to vary spatially in such a way as to encourage intra Region smoothing rather than interregion smoothing.
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