VLSI Architecture for Removing Impulse Noise in Images
Denoising Techniques
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Image Processing is widely used in many fields such as medical imaging, scanning techniques, printing skills, license plate recognition, face recognition and so on. Images are often corrupted by impulse noise during image acquisition and transmission. The noise may seriously affect the performance of image processing techniques. Impulse noise can be classified into two categories: Fixed valued impulse (Salt-and-Pepper) noise and Random-valued impulse noise. In fixed valued impulse noise the values are either 0 or 255 for gray scale images. In random - valued impulse noise the values are betwee...
Image Processing is widely used in many fields such as medical imaging, scanning techniques, printing skills, license plate recognition, face recognition and so on. Images are often corrupted by impulse noise during image acquisition and transmission. The noise may seriously affect the performance of image processing techniques. Impulse noise can be classified into two categories: Fixed valued impulse (Salt-and-Pepper) noise and Random-valued impulse noise. In fixed valued impulse noise the values are either 0 or 255 for gray scale images. In random - valued impulse noise the values are between 0 and 255 for gray scale images. In this project removal of salt-and-pepper noise from the corrupted image is focused. For this an efficient denoising scheme and a low cost, a low- complexity VLSI architecture is proposed. The technique Average Median Decision- Tree-Based Denoising Method (AMDTBDM) consists of an impulse noise detector to detect the noisy pixels, and an average median filter to reconstruct the intensity values of noisy pixels
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