Restoration of Optical Coherence Tomography Images with the Help of Discrete Wavelet Transform
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 4
Abstract
The automated processing of Optical Coherence tomography images has main difficulty of presence of noise which varies over the entire image. We first segment the OCT image into two regions, one containing different layers of eye and the other which contains only noise. The similar rows which contain only noise are considered to model the noise and then we find the local threshold value in adaptive manner. We were formulating a novel algorithm for OCT image restoration which uses a threshold derived from mean and variance of discrete wavelet coefficients in different sub bands of noisy image (segment of OCT image containing only noise). The found threshold will be different for the two segments of the image and all their sub bands. KEYWORDS-Optical Coherence Tomography (OCT), Choroid, Retinal Pigment Epithelium (RPE), Otsu's method, Discrete wavelet transform (DWT), Inverse discrete Wavelet Transform (IDWT).The automated processing of Optical Coherence tomography images has main difficulty of presence of noise which varies over the entire image. We first segment the OCT image into two regions, one containing different layers of eye and the other which contains only noise. The similar rows which contain only noise are considered to model the noise and then we find the local threshold value in adaptive manner. We were formulating a novel algorithm for OCT image restoration which uses a threshold derived from mean and variance of discrete wavelet coefficients in different sub bands of noisy image (segment of OCT image containing only noise). The found threshold will be different for the two segments of the image and all their sub bands. KEYWORDS-Optical Coherence Tomography (OCT), Choroid, Retinal Pigment Epithelium (RPE), Otsu's method, Discrete wavelet transform (DWT), Inverse discrete Wavelet Transform (IDWT).The automated processing of Optical Coherence tomography images has main difficulty of presence of noise which varies over the entire image. We first segment the OCT image into two regions, one containing different layers of eye and the other which contains only noise. The similar rows which contain only noise are considered to model the noise and then we find the local threshold value in adaptive manner. We were formulating a novel algorithm for OCT image restoration which uses a threshold derived from mean and variance of discrete wavelet coefficients in different sub bands of noisy image (segment of OCT image containing only noise). The found threshold will be different for the two segments of the image and all their sub bands.
Authors and Affiliations
Vinod Kumar Netad.
Keywords
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