Wavelet Transform-Based Image Fusion

Wavelet transform-based image fusion technology has been successfully implemented through a graphical user interface (GUI). This interface allows users to perform various image processing operations, meeting diverse application requirements. The technology finds extensive applications in image enhancement, target detection, and image fusion domains. Through image fusion, multiple source images can be combined into a single composite image with richer information content and improved visual quality. The implementation typically involves key steps such as wavelet decomposition using functions like wavedec2() for 2D signals, coefficient fusion rules (maximum selection or weighted average), and wavelet reconstruction using waverec2(). The application of wavelet transform makes the fusion process more precise and efficient by preserving both frequency and spatial information. This wavelet-based approach typically employs algorithms like discrete wavelet transform (DWT) with fusion rules applied to approximation and detail coefficients separately. Overall, wavelet transform-based image fusion technology brings enhanced possibilities and development opportunities to the field of image processing, with common implementations including multi-resolution analysis and region-based fusion strategies.