In this paper, for infrared images, the image enhancement technique based on wavelet transform is studied, which is a process that automatically apply different filtering coefficient toward different directions. The algorithm, including the application of nonlinear anisotropic diffusion, is experienced to the enhancement of infrared images. For directional filtering, the structural feature at each pixel is analyzed by the eigen-analysis. If the analysis shows that the pixel belongs to the edge region, we then perform directional smoothing along the tangential direction of the edge to improve its continuity, while directional sharpening along the normal direction to enhance the contrast. Meanwhile, the noise in the homogeneous region has been reduced notably by applying the appropriate wavelet coefficient. The algorithm is so effective that it reduces the noise while enhancing the edge sharpness at the same time. The quantitative measurements along with the visual inspection were also compared and results showed the algorithm based on wavelet transform has the ability in enhancing the infrared image. The proposed algorithm is compared to the other regular noise-reducing algorithms. The experimental results show that the proposed algorithm considerably improves the infrared image quality without causing any noticeable artifacts. Out of the algorithms compared, our algorithm demonstrated the best performance.
Hongbin Jin, Chunxiao Fan, Quanyong Wang, Yong Li, "Improvement of Infrared Image Based on Directional Anisotropic Wavelet Transform" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Visual Information Processing and Communication VIII, 2017, pp 51 - 55, https://doi.org/10.2352/ISSN.2470-1173.2017.2.VIPC-406