A Novel Approach to Satellite Image Fusion Based on Half Up and Down Motion Blur

Abstract

The merging of digital images is a crucial phase in digital imaging processing. It facilitates the amalgamation of information from various images into a singular image for enhanced quality and clarity. This paper simulates motion blur with different block sizes of 3, 5, 7, 9, and 11 pixels. The point spread function is programmed to obtain a linear blur motion. Motion blur simulation is used for half of the image in two parts (top half and bottom half). Conventional approaches integrate corrupted grayscale images using operations like addition and multiplication, but the suggested novel techniques in this study rely on weights defined by standard deviations. The suggested approaches employ a color conversion procedure from the RGB (red, green, and blue) color system to the HSV (hue, saturation, and value) color space in order to combine the top and bottom halves of colored blur images. Added, distorted, and typical edges in the original image were detected for the upper, lower, and merged images. Edges are compared visually using different thresholds. Among the evaluated methods, the standard deviation-based fusion technique demonstrated the highest effectiveness in preserving and enhancing edge information.