Fusion denoising algorithm of optical coherence tomography image based on point-estimated and block-estimated

Optical coherence tomography (OCT), as a tool for biological research and clinical application, plays an important role in disease diagnosis. However, speckle noise can significantly reduce the quality of OCT images, and low-quality images have a negative impact on subsequent research and diagnosis. Therefore, we propose a novel fusion algorithm based on point-estimated and block-estimated to remove speckle noise. Our algorithm combines the advantages of the pointestimated and block-estimated methods, and the experimental results also show that the algorithm is superior to other state-of-the-art denoising methods in visual inspection.

Automated summary

Optical coherence tomography (OCT) is a key tool in biological research and clinical applications, but speckle noise can degrade image quality and hinder subsequent analysis. A novel fusion algorithm based on point-estimated and block-estimated methods is proposed to remove speckle noise, outperforming existing denoising methods according to experimental results.