Panoramic image stitching is a popular technique for combining numerous photographs to generate wide-angle views and high-resolution images, Image stitching entails matching the pictures, adjusting for camera location and orientation discrepancies, and mixing the images to form a smooth composite image. In this paper, we offer an implementation of panoramic image stitching using Image processing techniques in python. The suggested technique employs feature-based image alignment, which aligns pictures by utilizing feature points in the images. The detection of spatial differences between the pixels of the image is a key to detect feature points, which is resistant to changes in scale, rotation, and affine distortion. After aligning the photos, we generate a smooth composite image. The suggested approach is tested on a real-world picture collection, and the findings demonstrate that it can generate high-quality panoramic photos with good alignment and smooth blending. The suggested approach is simple and straightforward to apply, and it has applications in virtual reality, surveillance and security systems, and film and video creation.