Computerized automation of wavelet based denoising method to reduce speckle noise in OCT images

Optical coherence tomography (OCT) is an optical imaging technique that allows the visualization of living tissues in vivo. However, the speckle noise affects their diagnostic accuracy by degrading the quality of OCT images. Wavelet based denoising methods have been successful in reducing the speckle noise in past but they require a manual selection of few parameters for optimum denoising. We propose a computerized method to select these parameters by using an evolutionary technique called differential evolution (DE). The selection process is purely objective and does not require any assumption of parameters as opposed to the existing wavelet based denoising methods. The performance improvement by using our method has been quantified in terms of signal to noise ratio (SNR) improvement and resolution preservation. An improvement of more than 17% in signal to noise ratio(SNR) was achieved while the resolution was restored after the application of our method.