An Infrared and Visible Image Fusion Algorithm Based on LSWT-NSST

Abstract

Regarding the problems of image distortion, edge blurring, Gibbs phenomena in the traditional wavelet transform algorithm and the loss of subtle features in the Non-Subsampled Shearlet Transform (NSST), and considering the physical characteristics of infrared and visible images, an infrared and visible image fusion algorithm based on the Lifting Stationary Wavelet Transform (LSWT) and Non-Subsampled Shearlet Transform is proposed in this paper. First, since LSWT can quickly calculate and has all advantages of traditional WT, it is utilized to decompose infrared and visible images to obtain lowfrequency coefficients and multi-scale and multi-directional high-frequency coefficients, respectively. Second, NSST multi-scale decomposition is used to extract the target features and detailed features of the image from the high and low-frequency sub-bands to obtain new high and low-frequency sub-bands. Third, according to the physical characteristics that low and high-frequency coefficients represent, different fusion rules are designed. Discrete Cosine Transform (DCT) and Local Spatial Frequency (LSF) are introduced in the low-frequency sub-band, and LSF adaptive weighted fusion rules are used in the DCT domain. The fusion strategy improves the regional contrast in the high-frequency sub-band with the spectral characteristics of human vision. Finally, the Inverse Lifting Stationary Wavelet Transform (ILSWT) is used to reconstruct the fusion coefficients to obtain the final fused images. To verify the advantages of the proposed algorithm in this paper, the classic and advanced 9 IR and VI fusion algorithms are selected for subjective and objective comparison. In the objective evaluation, a comprehensive ranking index is designed based on 9 classical indicators. Simulation experiments with 10 IR and VI fusion algorithms prove that the proposed algorithm has better performance and flexibility. The results show that the proposed algorithm in this paper fuses the images with clear edges, prominent targets, and good visual perception, and it outperforms state-of-the-art image fusion algorithms.

An Efficient Algorithm to Highlight Details in Infrared and Visible Image Fusion

“…Processing the source image from different sensors on the same target or scene according to a certain strategy, removing redundant information, and performing multidirectional and multiangle fusion can obtain a more accurate fusion image that reflects the target scene information [2]. With the development of image fusion technology, the cost of hardware equipment is reduced, and more comprehensive and reliable detailed information can be obtained [3]. Therefore, infrared and visible light image fusion technology has been extensively studied by scholars [4].…”

“…Infrared sensors can perceive heat radiation of different wavelengths, which can capture hidden target contour information, and they have great night vision and fog penetration capabilities, but they cannot obtain detailed information and have poor resolution [6]. Visible light sensors characterize objects through spectral reflection, and the results have high resolution and rich background information, which are suitable for human visual perception, but the image quality is easily affected by the environment, especially at night and under low visibility conditions [3]. If the images from these two sensors are fused, i.e., the main target information is obtained from the infrared image, while the main detailed background information is obtained from the visible image, then the fused image can provide better target features and more detailed scene information [7].…”

“…Visible light sensors characterize objects through spectral reflection, and the results have high resolution and rich background information, which are suitable for human visual perception, but the image quality is easily affected by the environment, especially at night and under low visibility conditions [3]. If the images from these two sensors are fused, i.e., the main target information is obtained from the infrared image, while the main detailed background information is obtained from the visible image, then the fused image can provide better target features and more detailed scene information [7]. Therefore, infrared and visible image fusion technology is a research hotspot, and it plays a key role in target tracking and detection, face recognition and other fields [8], [9].…”