Mantosh Biswas

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In this paper, a hybrid image denoising method that is based on locally adaptive window-based maximum likelihood (LAWML) and NeighShrink. The LAWML is doubly stochastic process models which denoise an image by exploiting the dependency of local wavelet coefficients within each scale. The LAWML needs a global optimal neighboring window. The NeighShrink(More)
Removing impulse noise in digital images is one of the major challenges in digital image processing. Pixels in digital images get corrupted during transmission due to impulse noise. In this paper, we propose a modified decision based median filter that removes impulse noise from gray images. For noise removal from digital images, different types of median(More)
Degradation of underwater images is an atmospheric phenomenon which is a result of scattering and absorption of light. In this paper, we have defined a fusion based approach to enhance the visibility of underwater images. Our method uses only one single hazy image to derive the contrast improved and colour corrected versions of the original image. Further,(More)
The term Curvelet transform in the field of Image Processing is quite well known from past few years. Its ability to detect curved features and smooth areas in an image marks its huge importance in the area of image denoising. However the ability to denoise image depends upon the selection and application of threshold after doing Curvelet based(More)
With the growth of the internet and the increasing importance of emails in our daily lives, spams have become a common phenomenon posing serious threats, as it gives rise to undesired emails. Image spam is a type of email spam in which the textual message is embedded within an image presenting it as a picture. This paper proposes a Support Vector Machine(More)
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