Speckle Noise

Speckle noise, a granular interference pattern inherent in coherent imaging systems like ultrasound and optical coherence tomography (OCT), degrades image quality and hinders accurate analysis. Current research focuses on developing advanced denoising techniques, employing diverse approaches such as convolutional neural networks (CNNs), autoencoders (with and without skip connections), and diffusion probabilistic models, often integrated with techniques like block matching and transformations (e.g., Short-Time-Fourier-Transform, Hough-Transform). These improvements are crucial for enhancing diagnostic accuracy in medical imaging, improving the reliability of remote sensing data analysis, and enabling more sensitive astronomical observations. The ultimate goal is to achieve efficient and robust speckle reduction while preserving essential image details.