Application of Wavelet Transform in the Denoising of Optical Weak Coherence Signal in Human Eye Examination

Abstract

Axial biological parameters of the eyeball are an important basis for the diagnosis and treatment of various intraocular diseases. Accurate measurement of the eyeball axial parameters directly affects the diagnosis and treatment effect of intraocular diseases. The ocular axial parameters measured by optical interferometry have no contact, high accuracy, short measurement time, and good repeatability and reproducibility. But in the measurement process of the eyeball, due to the low reflectance of the human eye, the light signal intensity reflected from the fundus of the human eye belongs to the category of weak signal. Affected by the noise of the working environment, photoelectric devices and the detection circuit itself, the interference signal output by the detector is difficult to be accurately analyzed in the future. Based on the theory of wavelet transform, the wavelet threshold denoising algorithm is studied in this paper. Aiming at the problems existing in the soft and hard threshold functions, an improved method of threshold denoising is proposed. In MATLAB, Haar, Daubechies, Coiflets and Symlets wavelet basis functions are selected to perform simulation denoising processing on the signal with noise. According to the signal-to-noise ratio (SNR) after denoising, Sym8 wavelet basis function is selected to denoise the weakly coherent eyeball signal. The wavelet threshold denoising module is implemented in FPGA and applied to the measured human eye weakly coherent interference signal processing. The denoising effect is good and the signal quality is effectively improved.