Panoramic radiography is widely used in dental practice for its comprehensive view of the oral cavity, capturing teeth, jaws, temporomandibular joints, sinuses, and bone structures. However, its primary limitation is the inadequate depiction of internal soft and hard tissue structures. To address this, this study conducts a comparative analysis of five image enhancement techniques: Contrast-limited adaptive histogram equalization (CLAHE), sharpened-CLAHE (S-CLAHE), SG-homomorphic filtering, fast local Laplacian filtering, and Bothhat filtering, aiming to improve tissue visualization in dental panoramic images. The effectiveness of these methods was assessed through extensive quantitative and qualitative analyses. The quantitative evaluation was conducted using structural similarity metrics—structural content (SC), structural similarity index (SSIM), and normalized cross-correlation (NCC)—as well as contrast-based metrics, including mean squared error (MSE), absolute mean brightness error (AMBE), measure of enhancement (EME), entropy-based measure of enhancement (EMEE), and contrast improvement index (CII). The qualitative evaluation highlights the effectiveness of the Bothhat filtering method, which achieves optimal enhancement compared to other techniques by improving image contrast without introducing significant distortions. Additionally, it enhances the visualization of the inferior alveolar canal (IAC) nerve region while maintaining structural integrity and avoiding the introduction of unintended details. The quantitative results further validate its effectiveness, achieving a high peak signal-to-noise ratio (PSNR) of 27.3183, a low mean squared error (MSE) of 120.5723, and a high structural similarity index (SSIM) of 0.905.