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Title: A Novel Two-Stage Impulse Noise Removal Technique Based on Neural Networks and Fuzzy
Page Link: A Novel Two-Stage Impulse Noise Removal Technique Based on Neural Networks and Fuzzy -
Posted By: smart paper boy
Created at: Wednesday 10th of August 2011 01:54:26 PM
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A Novel Two-Stage Impulse Noise Removal Technique Based on Neural Networks and Fuzzy Decision
Introduction
Images corrupted by impulse noise.
Objectives of noise removal:-
- Suppress the noise.
- To preserve the sharpness of edge.
Two-Stage impulse noise removal techniques used:-
- Neural Networks
- Fuzzy Decision
Neural Network
Neural network: information processing paradigm inspired by biological nervous systems, such as our brain
Structure: large number of h ....etc

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Title: Salt-and-Pepper Noise Removal by Median-type Noise Detectors and Detail-preserving
Page Link: Salt-and-Pepper Noise Removal by Median-type Noise Detectors and Detail-preserving -
Posted By: seminar class
Created at: Saturday 07th of May 2011 01:35:21 PM
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Abstract
This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first
phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise
(noise candidates). In the second phase, the image is restored using a specialized regularization method
that applies only to those selected noise candidates. In terms of edge preservation and noise suppression,
our restored images show a significant improvement compared to those restored by using just nonlinear
filters or r ....etc

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Title: NOISE REMOVAL USING ADAPTIVE FILTERS
Page Link: NOISE REMOVAL USING ADAPTIVE FILTERS -
Posted By: seminar class
Created at: Friday 06th of May 2011 06:52:26 PM
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NOISE REMOVAL USING ADAPTIVE FILTERS
....etc

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Title: Fast Adaptive Bilateral Filter for Edge Enhancement And Noise Removal
Page Link: Fast Adaptive Bilateral Filter for Edge Enhancement And Noise Removal -
Posted By: seminar class
Created at: Monday 02nd of May 2011 04:43:10 PM
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Presented By
Archana H Sable


Introduction
 Face detection : Identify location and size human
faces in an image.
 Challenges : Variations of image appearance
 Pose (front, non-front).
 Occlusion.
 Presence or absence of structural components.
 Image orientation.
 illuminating condition.
 facial expression.
Adaptive Bilateral Filter
The ABF retains the general form of a bilateral filter, ....etc

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Title: Implementation of Median and Mean filters using Bit planes for noise removal in image
Page Link: Implementation of Median and Mean filters using Bit planes for noise removal in image -
Posted By: seminar class
Created at: Monday 07th of March 2011 02:21:23 PM
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presented by:
K.PRATHYUSHA
T.RAJ KUMAR
D.PAPARAO
G.SHIRISHA


Bit plane
A Bit plane consists of the bits corresponding to the same significant level in all the elements
For example, the most significant bit plane is formed by considering the most significant bit(MSB) of each elements
The elements of a gray scale image have a maximum value of 255 and hence can be represented in binary domain using 8 bits
Higher order Bit planes of an image carry a significant amount of visually relevant deta ....etc

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Title: adaptive bilateral filter for sharpness enhancem ent and noise removal matlab code
Page Link: adaptive bilateral filter for sharpness enhancem ent and noise removal matlab code -
Posted By:
Created at: Thursday 01st of March 2012 11:50:49 PM
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i need matlab code for my topic plzzzzzzzzzzzz help me out or atleast tell me some tips to complete my code ....etc

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Title: Adaptive bilateral filter for sharpness enhancement and noise removal
Page Link: Adaptive bilateral filter for sharpness enhancement and noise removal -
Posted By: seminar presentation
Created at: Thursday 13th of May 2010 11:48:59 AM
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Adaptive bilateral filter for sharpness enhancement and noise removal
Presented By:
Zhang B, Allebach JP.
Texas Instruments, Inc, TX 75243, USA.
Abstract
In this paper, we present the adaptive bilateral filter (ABF) for sharpness enhancement and noise removal. The ABF sharpens an image by increasing the slope of the edges without producing overshoot or undershoot. It is an approach to sharpness enhancement that is fundamentally different from the unsharp mask (USM). This new approach to slope restoration also differs significantl ....etc

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Title: matlab code for salt and pepper noise removal by median type noise detectors and detail preserving regularization
Page Link: matlab code for salt and pepper noise removal by median type noise detectors and detail preserving regularization -
Posted By:
Created at: Monday 22nd of July 2013 12:01:29 AM
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Dear Madam\sir,

I am a research student. i want the matlab codings for salt and pepper noise removal by median type noise detectors and detail preserving regularization for my project dissertation. ....etc

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Title: IMPLEMENTATION OF EDGE PRESERVING TECHNIQUES FOR EFFICIENT REMOVAL OF IMPULSE NOISE
Page Link: IMPLEMENTATION OF EDGE PRESERVING TECHNIQUES FOR EFFICIENT REMOVAL OF IMPULSE NOISE -
Posted By: seminar class
Created at: Tuesday 19th of April 2011 02:50:05 PM
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presented by:
MS.Radha,J.V.Sangeetha,S.Suba bala sathiy


ABSTRACT:
Image signals might be corrupted by Impulse noise in the process of signal acquisition and transmission. In this paper,an efficient VLSI implementation for removing impulse noise is presented.Our extensive experimental results show that the proposed technique preserves the edge features and obtains excellent performances in terms of quantitative evaluation and visual quality. The design requires only low computational complexity and two ....etc

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Title: Fuzzy Random Impulse Noise Removal From Color Image Sequences
Page Link: Fuzzy Random Impulse Noise Removal From Color Image Sequences -
Posted By: computer girl
Created at: Monday 04th of June 2012 07:42:26 PM
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Fuzzy Random Impulse Noise Removal
From Color Image Sequences




Abstract

In this paper, a new fuzzy filter for the removal of
random impulse noise in color video is presented. By working with
different successive filtering steps, a very good tradeoff between
detail preservation and noise removal is obtained. One strong filtering
step that should remove all noise at once would inevitably
also remove a considerable amount of detail. Therefore, the noise
is filtered step by step. In each step, noisy pixe ....etc

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