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Journal ArticleDOI

Guided filter and convolutional network based tracking for infrared dim moving target

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TLDR
A tracking algorithm that integrates the Guided Image Filter and the Convolutional neural network into the particle filter framework is presented to cope with the uncertainty of dim targets and outperforms several relative algorithms in the accuracy.
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This article is published in Infrared Physics & Technology.The article was published on 2017-09-01. It has received 20 citations till now. The article focuses on the topics: Composite image filter & Convolutional neural network.

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Citations
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Journal ArticleDOI

Robust Infrared Small Target Detection Using Multiscale Gray and Variance Difference Measures

TL;DR: An accurate and robust method for infrared small target detection using multiscale gray and variance difference measures is proposed to alleviate the impact of background fluctuation and improve the robustness of the method.
Journal ArticleDOI

A moving target extraction algorithm based on the fusion of infrared and visible images

TL;DR: This work constructs a framework for moving target extraction and tracking in infrared and natural images, and proposes the rough fuzzy set theory model based on the traditional frame difference method to extract targets accurately.
Proceedings ArticleDOI

An Adaptation of Cnn for Small Target Detection in the Infrared

TL;DR: The Convolutional Neural Network is adapted to extract the hidden features of small targets from infrared imagery with a proposed technique for a large amount of training data generation.
Journal ArticleDOI

Graph-Regularized Laplace Approximation for Detecting Small Infrared Target Against Complex Backgrounds

TL;DR: A novel graph-regularized Laplace low-rank approximation detecting model (GRLA) is developed for infrared dim target scenes and extended to a generalized framework by replacing different non-convex rank functions by an iterative optimization scheme.
Journal ArticleDOI

Improved small moving target detection method in infrared sequences under a rotational background

TL;DR: An improved method using an optical flow field, which can estimate and compensate for the rotational motion background, thus detecting a small moving target and providing an idea for the target interception algorithm under the condition that an infrared imaging seeker is overlooking.
References
More filters
Journal ArticleDOI

A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

TL;DR: Both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters are reviewed.
Journal ArticleDOI

Guided Image Filtering

TL;DR: The guided filter is a novel explicit image filter derived from a local linear model that can be used as an edge-preserving smoothing operator like the popular bilateral filter, but it has better behaviors near edges.
Journal ArticleDOI

Lucas-Kanade 20 Years On: A Unifying Framework

TL;DR: In this paper, a wide variety of extensions have been made to the original formulation of the Lucas-Kanade algorithm and their extensions can be used with the inverse compositional algorithm without any significant loss of efficiency.
Journal ArticleDOI

Robust Object Tracking with Online Multiple Instance Learning

TL;DR: It is shown that using Multiple Instance Learning (MIL) instead of traditional supervised learning avoids these problems and can therefore lead to a more robust tracker with fewer parameter tweaks.
Journal ArticleDOI

A Local Contrast Method for Small Infrared Target Detection

TL;DR: An effective small target detection algorithm inspired by the contrast mechanism of human vision system and derived kernel model is presented, which can improve the SNR of the image significantly.
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