What is image denoising, and why is it important?
Image denoising removes noise from images while preserving important details like edges and textures. It improves visual quality, ensures critical details are intact for applications like medical imaging or computer vision, and prepares images for tasks like segmentation or analysis.
What are the most common types of noise in images?
Common noise types include Gaussian noise (random intensity variations), salt-and-pepper noise (random black and white pixels), Poisson noise (photon-based variations in low light), and speckle noise (granular noise in radar or ultrasound). Identifying noise type is crucial for effective denoising.
What are the denoising methods provided by the platform?
MP-PCA (Marchenko-Pastur Principal Component Analysis), Non-local means and Patch2Self are provided by the platfrom.