Segmentation Based Sparse Reconstruction of Optical Coherence Tomography Images


We show the value of using a division advance for enhancing the execution of sparsity based picture reproduction calculations. In particular, we will center around retinal optical lucidness tomography (OCT) remaking and propose a novel division based reproduction structure with meager portrayal, named division based scanty recreation (SSR). The SSR technique utilizes consequently sectioned retinal layer data to develop layer-particular basic word references. Furthermore, the SSR technique productively misuses fix similitudes inside each fragmented layer to improve the reproduction execution. Our test results on clinical-review retinal OCT pictures show the adequacy and effectiveness of the proposed SSR strategy for both denoising and introduction of OCT pictures.


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