A Novel GLBD Impulse Noise Detection Scheme using FODH for MAF
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In digital image processing, removal of noise is a highly demanding area of research. Impulsive noise is common in images which arise at the time of image acquisition and or transmission of images. This book deals with implementation and comparison of modified median filters for removal of high density impulse noise and further explores on limitation of these filters by proposing and implementing a new filtering scheme viz., a novel impulse noise detection scheme for Gray Level Boundary Discrimination using First Order Derivative Histogram for Modified Adaptive Filter. Extensive simulation wor...
In digital image processing, removal of noise is a highly demanding area of research. Impulsive noise is common in images which arise at the time of image acquisition and or transmission of images. This book deals with implementation and comparison of modified median filters for removal of high density impulse noise and further explores on limitation of these filters by proposing and implementing a new filtering scheme viz., a novel impulse noise detection scheme for Gray Level Boundary Discrimination using First Order Derivative Histogram for Modified Adaptive Filter. Extensive simulation work carried out shows that proposed novel noised detection scheme outperforms other filters in terms of quantitative as well as qualitative measures. The features such as simplicity and reduced execution time of proposed scheme makes it suitable for real time image processing applications.
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