Terahertz image enhancement method combining contrast limited adaptive histogram equalization and edge information

Terahertz (THz) nondestructive testing technology faces limitations such as low imaging resolution, poor signal-to-noise ratio, and insufficient contrast. In this work, we propose a THz image enhancement method that combines contrast limited adaptive histogram equalization (CLAHE) with edge information. The method first employs Gaussian low-pass filtering to suppress high-frequency noise. Subsequently, the CLAHE algorithm is used to achieve local contrast adjustment. Then, the Canny operator is adopted to detect and extract features from the original image. Finally, a weighted fusion of the enhanced image and the edge map is performed to balance detail enhancement and noise suppression. Experimental results show significant improvements in objective metrics: the mean gradient (MG) increased by over 66%. The Tenengrad sharpness metric increased by more than 46% and the structural similarity index (SSIM) was maintained at approximately 0.8. Compared with existing methods, the proposed method effectively enhances edge sharpness and contrast while preserving the structural integrity of the image. Therefore, we provide an effective software-based enhancement solution for the THz image enhancement, which is very useful for nondestructive testing.