###### Abstract  
Contrast enhancement techniques serve the purpose of diminishing image noise and increasing the contrast of relevant structures. In the context of medical images, where the differentiation between normal and abnormal tissues can be quite subtle, precise interpretation might become challenging when noise levels are relatively elevated. The Fast Local Laplacian Filter (FLLF) is proposed to deliver a more precise interpretation and present a clearer image to the observer; this is achieved through the reduction of noise levels. In this study, the FLLF strengthened images through its unique contrast enhancement capabilities while preserving important image details. It achieved this by adapting to the image's characteristics and selectively enhancing areas with low contrast, thereby improving the overall visual quality. Additionally, the FLLF excels in edge preservation, ensuring that fine details are retained and that edges remain sharp. Several performance metrics were employed to assess the effectiveness of the proposed technique. These metrics included Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Normalization Coefficient (NC), and Correlation Coefficient. The results indicated that the proposed technique achieved a PSNR of 40.12, an MSE of 8.6982, an RMSE of 2.9492, an NC of 1.0893, and a Correlation Coefficient of 0.9999. The analysis highlights the superior performance of the proposed method when contrast enhancement is applied, especially when compared to existing techniques. This approach results in high-quality images with minimal information loss, ultimately aiding medical experts in making more accurate diagnoses. 23 September 20  
in facilitating medical interventions and treatments for issues such as vessel narrowing, blockages, and other conditions, particularly those impacting the heart. Despite its clinical significance, angiography images often exhibit variations in contrast, brightness, and overall quality due to diverse imaging conditions and patient characteristics [2]. Such variability can hinder accurate diagnosis and analysis, underscoring the need for advanced contrast enhancement techniques to improve the visibility of blood vessels and intricate vascular structures [3]. In recent years, digital image processing has emerged as a powerful tool for enhancing the quality of medical images, thereby facilitating more precise medical evaluations and diagnoses. Among the array of techniques available, contrast enhancement has garnered substantial attention due to its ability to improve image clarity and optimize visual information. This study delves into the application of the Fast Local Laplacian Filter (FLLF) technique for enhancing blood vessel contrast in coronary angiography images [4]. Modern medical imaging relies on digital processing methodologies to elevate image quality and extract crucial diagnostic information [5]. Contrast enhancement, in particular, has emerged as a promising avenue to amplify the visibility of relevant structures, thereby facilitating more accurate and confident clinical interpretations [6; 7; 8; 9]. This study capitalizes on the Fast Local Laplacian Filter technique's potential to enhance contrast while maintaining image details and minimizing undesirable artifacts. The central objective of this study is to explore the effectiveness of Fast Local Laplacian Filter techniques in enhancing blood vessel contrast within coronary angiography images [10; 11]. In the FLLF technique, a Laplacian pyramid is created to capture local image variations and details at different scales. After that, the modified Laplacian (ML) is introduced through a bilateral filter applied to each level of the Laplacian pyramid. This bilateral filter is controlled by two factors: the spatial distance (d) and the range similarity (r). It effectively preserves edges, reduces noise, and enhances image contrast.