Multi-Exposure Fusion

Multi-focus image fusion based on the Mallat algorithm is a technique that combines multiple images captured at different focal lengths. By integrating information from these images, this method produces clearer, more detailed composite images. The implementation typically involves wavelet decomposition using the Mallat algorithm, which applies multi-resolution analysis through discrete wavelet transform (DWT). Key steps include: 1) Decomposing source images into high-frequency (detail) and low-frequency (approximation) coefficients using wavelet filters, 2) Implementing fusion rules (like maximum selection or weighted averaging) for coefficient recombination, and 3) Reconstructing the fused image through inverse DWT. This approach finds applications in computer vision, medical imaging, and other fields where it enhances image quality and sharpness, providing more accurate information for image analysis and processing tasks. The method is particularly valuable for improving depth-of-field limitations in optical systems.