Hybrid Image De-Noising using Wavelet
Grouping with PCA
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The modern era of visual description of technology, an easier and interesting approach, demands an image exclusive of any sort of noise. The images usually bring different kinds of noise in the process of receiving, coding and transmission. The occurrence of noise in images of different modalities due to random variation degrades the quality of image. This increases an important issue of de-noising the images for generating a good quality image. There are many types of noises viz Salt & Pepper noise, Gaussian noise etc. which can decrease the quality of images. Image de-noising is an objective...
The modern era of visual description of technology, an easier and interesting approach, demands an image exclusive of any sort of noise. The images usually bring different kinds of noise in the process of receiving, coding and transmission. The occurrence of noise in images of different modalities due to random variation degrades the quality of image. This increases an important issue of de-noising the images for generating a good quality image. There are many types of noises viz Salt & Pepper noise, Gaussian noise etc. which can decrease the quality of images. Image de-noising is an objective restoration process, in which our main aim is to recover an image that has been degraded by having prior knowledge. In previous decades de-noising of images were done using filtering techniques, methods and so far a lot of filtering methods. A lot of filtering methods have been proposed by the researchers in literature such as Wiener filtering and Wavelet based thresholding approach having Gaussian Noise.
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