OCT image denoising algorithm based on discrete wavelet transform and spatial domain feature fusion

AbstractOptical coherence tomography (OCT) is an emerging optical imaging modality with high resolution and non-invasive, which plays an important role in applications such as material detection and disease diagnosis, especially for ophthalmic retinal diseases such as age-related macular degeneration, diabetic macular edema and choroidal neovascularization. However, since OCT utilizes the coherent interference of light, the generated image is inevitably affected by speckle noise, which blurs the structural information of the image such as layer structure and lesion point, and the low-quality OCT image makes its subsequent application become difficult. To solve this problem, an OCT image denoising fusion based on discrete wavelet transform and spatial domain feature weighting is proposed in this paper. Extensibility experiments show that the proposed algorithm can better remove noise and retain its precise structural information compared with several state-of-the-art OCT image denoising algorithms.Keywords: Image fusionimage denoisingoptical coherence tomographyspeckle noisediscrete wavelet transform Disclosure statementThe authors have no relevant financial interests in this article and no potential conflicts of interest to disclose.Additional informationFundingThis research is supported in part by the Natural Science Foundation of Shandong Province of China [grant numbers ZR2021QA062, ZR2019MF045] and the National Natural Science Foundation of China [grant numbers 12071263, 11971269, 11971272] .