Robust infrared small target detection using local steering kernel reconstruction

This paper advocates the local steering kernel to encode the image patch.A novel local adaptive contrast measure using local steering kernel is proposed.This paper presents a patch-based infrared small target detection approach.The proposed infrared small target detection method achieves promising results. Because infrared small target detection plays a crucial role in infrared monitoring and early warning systems, it has been the subject of considerable research. Although many infrared small target detection approaches have been proposed, how to robustly detect small targets in poor quality infrared images remains a challenge. Since existing feature descriptors are often sensitive to the quality of infrared images, this paper advocates the use of a local steering kernel (LSK) to encode the infrared image patch because the LSK method can provide robust estimation of local intrinsic structure, even for poor quality images. Furthermore, this paper proposes a novel local adaptive contrast measure based on LSK reconstruction (LACM-LSK) for infrared small target detection. To demonstrate the effectiveness of the proposed approach, a diverse test dataset, including six infrared image sequences with different backgrounds, was collected. Extensive experiments on the test dataset confirm that the proposed infrared small target detection approach can achieve better detection performance than state-of-the-art approaches.

[1]  Jie Ma,et al.  A Robust Directional Saliency-Based Method for Infrared Small-Target Detection Under Various Complex Backgrounds , 2013, IEEE Geoscience and Remote Sensing Letters.

[2]  Xiangzhi Bai,et al.  Analysis of new top-hat transformation and the application for infrared dim small target detection , 2010, Pattern Recognit..

[3]  Ji Zhao,et al.  Good match exploration for infrared face recognition , 2014 .

[4]  Yongjun Zhang,et al.  Large-Scale Remote Sensing Image Retrieval by Deep Hashing Neural Networks , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Meng Hwa Er,et al.  Max-mean and max-median filters for detection of small targets , 1999, Optics & Photonics.

[6]  Yihua Tan,et al.  Cauchy graph embedding based diffusion model for salient object detection. , 2016, Journal of the Optical Society of America. A, Optics, image science, and vision.

[7]  Tamar Peli,et al.  Morphology-based algorithm for point target detection in infrared backgrounds , 1993, Defense, Security, and Sensing.

[8]  Fan Fan,et al.  A Robust Infrared Small Target Detection Algorithm Based on Human Visual System , 2014, IEEE Geoscience and Remote Sensing Letters.

[9]  Peyman Milanfar,et al.  Kernel Regression for Image Processing and Reconstruction , 2007, IEEE Transactions on Image Processing.

[10]  Yi Yang,et al.  Infrared Patch-Image Model for Small Target Detection in a Single Image , 2013, IEEE Transactions on Image Processing.

[11]  Peyman Milanfar,et al.  Training-Free, Generic Object Detection Using Locally Adaptive Regression Kernels , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Xiao Sun,et al.  Infrared small target detection via line-based reconstruction and entropy-induced suppression , 2016 .

[13]  Sungho Kim,et al.  Scale invariant small target detection by optimizing signal-to-clutter ratio in heterogeneous background for infrared search and track , 2012, Pattern Recognit..

[14]  Jing Chen,et al.  Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online , 2014, Sensors.

[15]  Xin Zhou,et al.  Infrared small-target detection using multiscale gray difference weighted image entropy , 2016, IEEE Transactions on Aerospace and Electronic Systems.

[16]  Jiayi Ma,et al.  Infrared and visible image fusion via gradient transfer and total variation minimization , 2016, Inf. Fusion.

[17]  Chenming Li,et al.  A robust infrared dim target detection method based on template filtering and saliency extraction , 2015 .

[18]  Peyman Milanfar,et al.  Static and space-time visual saliency detection by self-resemblance. , 2009, Journal of vision.

[19]  Bo Du,et al.  Target Detection Based on Random Forest Metric Learning , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[20]  Yantao Wei,et al.  Small target detection based on weighted self-information map , 2013 .

[21]  Michael Elad,et al.  Super-Resolution Without Explicit Subpixel Motion Estimation , 2009, IEEE Transactions on Image Processing.

[22]  Sheng Zheng,et al.  Multiscale facet model for infrared small target detection , 2014 .

[23]  Yuan Yan Tang,et al.  A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[24]  Xinge You,et al.  Local Metric Learning for Exemplar-Based Object Detection , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[25]  Shengxiang Qi,et al.  A fast-saliency method for real-time infrared small target detection , 2016 .

[26]  Jinwen Tian,et al.  Infrared small target detection using directional highpass filters based on LS-SVM , 2009 .

[27]  Xin Zhou,et al.  Small Infrared Target Detection Based on Weighted Local Difference Measure , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[28]  Hang Li,et al.  Infrared small target enhancement via phase spectrum of Quaternion Fourier Transform , 2014 .

[29]  Xin Huang,et al.  Unsupervised Deep Feature Learning for Urban Village Detection from High-Resolution Remote Sensing Images , 2017 .

[30]  G.-D. Wang,et al.  Facet-based infrared small target detection method , 2005 .

[31]  Yihua Tan,et al.  Kernel regression in mixed feature spaces for spatio-temporal saliency detection , 2015, Comput. Vis. Image Underst..

[32]  Yongjun Zhang,et al.  A novel spatio-temporal saliency approach for robust dim moving target detection from airborne infrared image sequences , 2016, Inf. Sci..

[33]  Junjun Jiang,et al.  Robust Feature Matching for Remote Sensing Image Registration via Locally Linear Transforming , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[34]  Yihua Tan,et al.  Unsupervised Multilayer Feature Learning for Satellite Image Scene Classification , 2016, IEEE Geoscience and Remote Sensing Letters.

[35]  Alan L. Yuille,et al.  Non-Rigid Point Set Registration by Preserving Global and Local Structures , 2016, IEEE Transactions on Image Processing.

[36]  Yantao Wei,et al.  Multiscale patch-based contrast measure for small infrared target detection , 2016, Pattern Recognit..

[37]  Yantao Wei,et al.  Small infrared target detection based on image patch ordering , 2016, Int. J. Wavelets Multiresolution Inf. Process..

[38]  Yuan Yan Tang,et al.  A Local Contrast Method for Small Infrared Target Detection , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[39]  Yihua Tan,et al.  Biologically inspired multilevel approach for multiple moving targets detection from airborne forward-looking infrared sequences. , 2014, Journal of the Optical Society of America. A, Optics, image science, and vision.

[40]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[41]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).