Denoising of Digital Images using Hybrid Computing
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With the growth of multimedia technology over the past few decades, the demand for digital information has increased dramatically. Digital images are often corrupted by noise during their acquisition or transmission. A number of different noises exists in the image processing system. These includes the Salt-and-Pepper noise, Gaussian noise and Speckle noise. In order to extract complete information from an image, it is essential that the images acquired be free of noise. Denoising of images, is thus, a very important aspect of image processing. For denoising images corrupted with these noises,...
With the growth of multimedia technology over the past few decades, the demand for digital information has increased dramatically. Digital images are often corrupted by noise during their acquisition or transmission. A number of different noises exists in the image processing system. These includes the Salt-and-Pepper noise, Gaussian noise and Speckle noise. In order to extract complete information from an image, it is essential that the images acquired be free of noise. Denoising of images, is thus, a very important aspect of image processing. For denoising images corrupted with these noises, a number of hybrid techniques have been presented in this book in a very lucid manner using various techniques and methods including Statistical methods, Wavelets and Wavelet Packets, Soft Computing methods and Total Variational Approach. The book would open the gates for further development of improved hybrid techniques for denoising images corrupted with one or more types of noise.
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