Single Scale Alignment, often used in image processing and computer vision, refers to the technique of aligning two images so that they match with each other in terms of scale, rotation, and translation, but only at one scale level. This means that if there are variations in size and scale between the two images, the alignment process does not account for multi-scale features or transformations; it assumes that the images are already at the same scale or that a single uniform scaling factor can be applied to match them. while using a window to align channels can be effective for low-resolution images, this approach becomes impractical for higher-resolution images due to the increased computational cost. Additionally, reducing the window size to mitigate computational demands risks missing the optimal alignment shift, especially if the best shift falls outside the smaller window.