Evaluation Of Noise In Dna Fingerprint Images Produced By

Abstract

DNA fingerprint images produced by hybridization techniques are often degraded by different types of noise such as film grain noise and noise from electrophoresis, membrane, hybridization process, etc. The purpose of noise reduction is to obtain an image that differ as little as possible from the noise free image. The basic difficulty of the noise reduction technique is that, if applied indiscriminately, they tend to blur the image. Further, the effectiveness of each noise reduction technique tends to be affected by the type of noise to be filtered and the characteristics of the image to be processed. To perform an effective noise filtering, a noise model which describes the noise type is required. Methods such as SVD (Singular Value Decomposition) with power spectrum and local statistics (such as mean and variance) are applied to estimate the noise characteristics in hybridized DNA fingerprint images. The results obtained indicate that these type of images are affected by both additive and multiplicative noise. Homomorphic low pass filter and iterative KNN (K nearest neighbor) filter are applied to reduce the noise