Infrared Dim and Small Target Detection Based on the Improved Tensor Nuclear Norm

Abstract

In the face of complex scenes with strong edge contours and high levels of noise, suppressing edge contours and noise levels is challenging with infrared dim and small target detection algorithms. Many advanced algorithms suffer from high false alarm rates when facing this problem. To solve this, a new anisotropic background feature weight function based on the infrared patch tensor (IPT) model was developed in this study to characterize the background airspace difference features by effectively combining the local features with the global features to suppress the strong edge contours in the structural tensor. Secondly, to enhance the target energy in the a priori model, an improved high-order cumulative model was proposed to establish the local significance region of the target as a way to achieve energy enhancement of the significant target in the structural tensor. Finally, the energy-enhanced structural tensor was introduced into the partial sum of the sensor nuclear norm (PSTNN) model as a local feature information weight matrix; the detection results were obtained by solving the model with the help of ADMM. A series of experiments show that the algorithm in this paper achieves better detection results compared with other algorithms.

An Infrared Target Images Recognition and Processing Method Based on the Fuzzy Comprehensive Evaluation

“…Miao et al [9] put forward a single-frame infrared weak target detection algorithm based on improved Sobel operator, the improved Sobel operator is used to convolve the image, and finally detected infrared weak and small targets after median filtering. Yuan et al [10] researched an infrared weak target detection algorithm based on randomized tensor algorithm, which not only reduced the computational complexity, but also improved the detection performance of infrared weak and small targets compared with the traditional algorithm based on low-rank sparse decomposition. Xiong et al [11] presented a millimeter-wave radar and infrared camera fusion system, which extracts and combines the advantage information of each sensor through target-level fusion, and finally output stable target perception results.…”